JP6586945B2 - Ship allocation plan creation method, ship allocation plan creation device - Google Patents
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Description
本発明は、配船計画作成方法、配船計画作成装置、及び製鉄所の運用方法に関する。 The present invention relates to a ship assignment plan creation method, a ship assignment plan creation apparatus, and a method for operating a steelworks.
製鉄所では日々、海外から輸送されてきた原料を用いて鉄鋼製品を生産している。製鉄所では複数の原料を配合して鉄鋼製品の成分を調整する必要があり、高品質な鉄鋼製品を安定的に生産するためには、複数種類の原料を製鉄所に安定的に供給することが重要である。また、鉄鋼製品のコストを低減するためには、原料の輸送コストを抑制する必要がある。原料の輸送コストには、船の傭船コストや契約した予定日数より多くの荷役日数を要した場合に船主に支払う滞船料等がある。 Steel mills produce steel products every day using raw materials that have been transported from overseas. In steelworks, it is necessary to adjust the components of steel products by blending multiple raw materials, and in order to stably produce high-quality steel products, it is necessary to stably supply multiple types of raw materials to steelworks. is important. Moreover, in order to reduce the cost of steel products, it is necessary to suppress the transportation cost of raw materials. The transportation cost of raw materials includes ship dredging costs and berthing fees that are paid to the shipowner when the number of cargo handling days is longer than the scheduled number of contracts.
海外の積地は複数あり、各積地で船に荷積みできる成分の異なる原料の銘柄は複数ある。また、原料を荷揚げする揚地も複数存在する。このため、寄港する積地、荷積みする銘柄、荷積み量、揚地、荷揚げする銘柄、及び荷揚げ量を各航海について定めた配船計画には多数の取り得る組合せが考えられる。こうした多数の組合せの中から原料の安定供給及び輸送コスト削減の観点で最適解を得るために、数理計画法やメタヒューリスティクス等の最適化技術を用いた各種の配船計画作成方法が提案されている。 There are multiple overseas loading sites, and there are several brands of raw materials with different ingredients that can be loaded onto ships at each loading site. There are also several landing sites where the raw materials are unloaded. For this reason, there are many possible combinations for the loading place where the port of call, the brand to be loaded, the amount to be loaded, the landing place, the brand to be unloaded, and the amount to be unloaded are determined for each voyage. In order to obtain an optimal solution from the viewpoint of stable supply of raw materials and reduction of transportation costs from these many combinations, various ship allocation plan creation methods using optimization techniques such as mathematical programming and metaheuristics have been proposed. ing.
例えば特許文献１には、各輸送手段の運行順序及び輸送物品の品種の設定と当該設定を元に各輸送物品の品種毎の到着日及び到着量を算出するシミュレーションとを繰り返し実行し、メタヒューリスティクスを用いて最適な物流計画を作成する発明が記載されている。また、特許文献２には、船舶毎に運航可能な積地及び揚地の組み合せパターンと揚地での需給バランス制約を表す数式モデルとを作成し、数理計画法を用いて最適化計算を実行後、シミュレーションにより詳細な配船計画を立案する発明が記載されている。 For example, in Patent Document 1, the setting of the operation sequence of each means of transportation and the type of transportation article and the simulation for calculating the arrival date and the arrival amount for each kind of each transportation article based on the setting are repeatedly executed. An invention for creating an optimal logistics plan using tics is described. Also, in Patent Document 2, a combination pattern of loading and landing sites that can be operated for each ship and a mathematical model that expresses a balance between supply and demand at the landing site are created, and optimization calculation is performed using mathematical programming. Later, an invention for making a detailed ship allocation plan by simulation is described.
しかしながら、特許文献１記載の発明では、１回の運行で対象としている揚地は１か所であり、複数の揚地を取り得る場合は考慮されていない。また、特許文献２記載の発明では、１回の航海で寄港する積地は１か所となっており、今回の１回の航海で複数の積地に寄港する多港積みは考慮されていない。 However, in the invention described in Patent Document 1, there is only one landing site that is targeted for one operation, and a case where a plurality of landing sites can be taken is not considered. Moreover, in the invention described in Patent Document 2, there is only one loading place that calls at one voyage, and multi-port loading that calls at multiple loading places at this one voyage is not considered. .
本発明は、上記課題に鑑みてなされたものであって、その目的は、原料の安定供給及び輸送コストの最小化を両立させた複数の積地から複数の揚地への配船計画を作成可能な配船計画作成方法及び配船計画作成装置を提供することである。また、本発明の他の目的は、高品質な鉄鋼製品を安定的に、且つ、低コストで生産可能な製鉄所の運用方法を提供することである。 The present invention has been made in view of the above problems, and its purpose is to create a ship allocation plan from a plurality of loading sites to a plurality of landing sites that achieves both stable supply of raw materials and minimization of transportation costs. It is to provide a possible ship allocation plan creation method and a ship allocation plan creation apparatus. Another object of the present invention is to provide a method of operating a steel mill capable of producing high-quality steel products stably and at low cost.
本発明に係る配船計画作成方法は、コンピュータを用いて構築された配船計画作成装置において、コンピュータが、製品の製造に必要な各種原料を複数の積地から複数の揚地へ船で輸送する配船計画を作成する配船計画作成方法であって、コンピュータが備えるデータ読み込み部が、少なくとも前記船の属性情報及び動静情報、各積地と各揚地との間の航海日数、地区要求予定情報、計画期間の間における各積地での銘柄単位積載予定合計量の情報を読み込むデータ読み込みステップと、コンピュータが備える最適化モデル作成部が、ある地点から他の地点への移動に航海日数及び荷役時間を考慮する制約、船の積載可能量を考慮する制約、及び各地区の要求予定を満たして船の積載内容及び荷揚内容を決める制約を含めた制約とし、少なくとも滞船料コストを評価関数とし、前記制約と前記評価関数を数式で表し、該評価関数を最小化する最適化モデルを作成する最適化モデル作成ステップと、コンピュータが備える最適化モデル計算部が、前記制約に従って前記最適化モデルを数理最適化手法により解くことによって配船計画を作成する最適化モデル計算ステップと、を含むことを特徴とする。 The ship allocation plan creation method according to the present invention is a ship allocation plan creation apparatus constructed using a computer, in which the computer transports various raw materials necessary for manufacturing products from a plurality of loading sites to a plurality of landing sites by ship. A ship allocation plan creation method for creating a ship allocation plan, wherein a data reading unit included in the computer includes at least attribute information and movement information of the ship, the number of days of voyage between each loading place and each landing place, and district requirements The data reading step that reads the schedule information and the information of the total planned loading amount of each brand at each loading point during the planning period, and the optimization model creation section provided in the computer, the number of voyage days to move from one point to another In addition, there are few restrictions, including restrictions that consider the handling time, restrictions that consider the load capacity of the ship, and restrictions that determine the loading and unloading contents of the ship that meet the requirements of each region. And the optimization model creating step for creating an optimization model for minimizing the evaluation function, and an optimization model calculation unit included in the computer. And an optimization model calculation step of creating a ship allocation plan by solving the optimization model by a mathematical optimization method in accordance with the constraint.
本発明に係る配船計画作成方法は、上記発明において、前記最適化モデル計算ステップは、コンピュータが備える最適化モデル計算部が、各地区の要求予定を満たせなかった原料の分量を算出し、算出された分量をペナルティとして前記評価関数に追加するステップを含むことを特徴とする。 In the ship allocation plan creation method according to the present invention, in the above-mentioned invention, the optimization model calculation step calculates an amount of the raw material that the optimization model calculation unit included in the computer fails to satisfy the required schedule of each district, and calculates Adding the determined amount as a penalty to the evaluation function.
本発明に係る配船計画作成方法は、上記発明において、前記最適化モデル作成ステップは、コンピュータが備える最適化モデル作成部が、離散的な時間毎に生成された各地点に対応するノードと該ノード間を結ぶパスとからなる時空間ネットワークを用いて前記制約及び前記評価関数を数式で表すことを特徴とする。 In the ship allocation plan creation method according to the present invention, in the above invention, in the optimization model creation step, the optimization model creation unit provided in the computer includes a node corresponding to each point generated at discrete time intervals and the node. The constraint and the evaluation function are expressed by mathematical expressions using a spatio-temporal network including paths connecting nodes.
本発明に係る配船計画作成方法は、上記発明において、前記データ読み込みステップは、コンピュータが備えるデータ読み込み部が、原料の銘柄のグルーピングを設定した銘柄区分情報を読み込み、銘柄単位積載予定合計量の情報から銘柄区分毎に集約した銘柄区分単位積載予定合計量の情報を作成するステップを含み、前記最適化モデル作成ステップは、コンピュータが備える最適化モデル作成部が、銘柄区分単位積載予定合計量の情報を用いて銘柄区分単位の最適化モデルを作成するステップと、コンピュータが備える最適化モデル作成部が、銘柄区分単位の最適化モデルを解くことによって得られる銘柄区分単位の荷積み量及び荷揚げ量を用いて銘柄単位での荷積み量及び荷揚げ量を決定する銘柄区分内容決定モデルを作成するステップと、を含み、前記最適化モデル計算ステップは、コンピュータが備える最適化モデル計算部が、銘柄区分単位の最適化モデルを解いた後に前記銘柄区分内容決定モデルを解くステップを含むことを特徴とする。 In the above-mentioned invention, the data read-out step of the data read-out step provided in the computer reads in the stock classification information in which the stock brand groupings are set, and the total load of the stock unit is estimated. Including a step of creating information on the total scheduled loading amount of the brand classification unit aggregated for each brand classification from the information, wherein the optimization model creating step includes an optimization model creating unit provided in the computer for the total loading amount of the brand classification unit. The step of creating an optimization model for each stock classification unit using information, and the optimization model creation unit provided in the computer solves the optimization model for each stock classification unit, and the loading amount and unloading amount for each stock classification unit Step to create a stock category content determination model that determines the loading and unloading amount in stock units using And the optimization model calculation step includes a step in which an optimization model calculation unit provided in the computer solves the stock category content determination model after solving the stock category unit optimization model. .
本発明に係る配船計画作成装置は、コンピュータを用いて構築された、製品の製造に必要な各種原料を複数の積地から複数の揚地へ船で輸送する配船計画を作成する配船計画作成装置であって、少なくとも前記船の属性情報及び動静情報、各積地と各揚地との間の航海日数、地区要求予定情報、計画期間の間における各積地での銘柄単位積載予定合計量の情報を読み込むデータ読み込み部と、ある地点から他の地点への移動に航海日数及び荷役時間を考慮する制約、船の積載可能量を考慮する制約、及び各地区の要求予定を満たして船の積載内容及び荷揚内容を決める制約を含めた制約とし、少なくとも滞船料コストを評価関数とし、前記制約と前記評価関数を数式で表し、該評価関数を最小化する最適化モデルを作成する最適化モデル作成部と、前記制約に従って前記最適化モデルを数理最適化手法により解くことによって配船計画を作成する最適化モデル計算部と、を備えることを特徴とする。 A ship allocation plan creation device according to the present invention is a ship allocation plan that uses a computer to create a ship allocation plan for transporting various raw materials necessary for manufacturing products from a plurality of loading sites to a plurality of landing sites. A plan creation device, which includes at least the attribute information and movement information of the ship, the number of days of voyage between each loading site and each landing site, the district request schedule information, and the loading schedule for each brand at each loading site during the planning period The data reading unit that reads the total amount of information, the restrictions that consider the days of voyage and the cargo handling time for moving from one point to another, the restrictions that consider the load capacity of the ship, and the required schedule of each region are satisfied. Create an optimization model that includes constraints that determine the contents of loading and unloading of the ship, at least the stagnation fee cost as an evaluation function, expresses the constraints and the evaluation function in mathematical formulas, and minimizes the evaluation function Optimization model creation When, characterized in that it comprises a and optimization model calculation unit for creating a Sailing plan by solving the optimization model by mathematical optimization method in accordance with the constraints.
本発明に係る製鉄所の運用方法は、本発明に係る配船計画作成方法によって作成された配船計画に基づいて輸送されてきた原料を用いて鉄鋼製品を生産するステップを含むことを特徴とする。 The method for operating a steel mill according to the present invention includes a step of producing steel products using raw materials that have been transported based on a ship allocation plan created by the ship allocation plan creation method according to the present invention. To do.
本発明に係る配船計画作成方法及び配船計画作成装置によれば、原料の安定供給及び輸送コストの最小化を両立させた複数の積地から複数の揚地への配船計画を作成することができる。また、本発明に係る製鉄所の運用方法によれば、高品質な鉄鋼製品を安定的に、且つ、低コストで生産することができる。 According to the ship allocation plan creation method and the ship allocation plan creation apparatus according to the present invention, a ship allocation plan from a plurality of loading sites to a plurality of landing sites that achieves stable supply of raw materials and minimization of transportation costs is created. be able to. Moreover, according to the operation method of the steelworks which concerns on this invention, a high quality steel product can be produced stably and at low cost.
以下、図面を参照して、本発明の一実施形態である配船計画作成システムの構成及びその動作について説明する。 Hereinafter, with reference to the drawings, a configuration and operation of a ship allocation plan creation system according to an embodiment of the present invention will be described.
〔構成〕
まず、図１を参照して、本発明の一実施形態である配船計画作成システムの構成について説明する。
〔Constitution〕
First, with reference to FIG. 1, the structure of the ship allocation plan preparation system which is one Embodiment of this invention is demonstrated.
図１は、本発明の一実施形態である配船計画作成システムの構成を示すブロック図である。図１に示すように、本発明の一実施形態である配船計画作成システム１は、属性情報・動静情報データベース（ＤＢ）２ａ、入港制約情報ＤＢ２ｂ、バース情報ＤＢ２ｃ、航海日数情報ＤＢ２ｄ、各地区要求予定情報ＤＢ２ｅ、銘柄単位積載予定合計量情報ＤＢ２ｆ、配船計画作成装置３、及び配船計画ＤＢ４を主な構成要素として備えている。 FIG. 1 is a block diagram showing a configuration of a ship allocation plan creation system according to an embodiment of the present invention. As shown in FIG. 1, a ship allocation plan creation system 1 according to an embodiment of the present invention includes an attribute information / movement information database (DB) 2a, a port entry restriction information DB 2b, a berth information DB 2c, a voyage day information DB 2d, and each district. The request schedule information DB 2 e, the brand unit scheduled load total information DB 2 f, the ship allocation plan creation device 3, and the ship allocation plan DB 4 are provided as main components.
属性情報・動静情報ＤＢ２ａは、以下の表１に示すような、原料の輸送に使用する船の属性情報及び船が配船計画作成時に従事している航海を終え、次航海へ出航できる予定日（次航海可能日）を示す動静情報を格納している。ここで、船の属性情報には、船ＩＤ、バースへの入港可否を考慮する上で必要となるサイズ、船主との契約内容、揚げラン（１日に荷揚げ可能な原料の重量）、デスレート（予定滞船日数より実際の滞船日数が短かった場合に船主から契約者に支払うレート）、デマレート（予定滞船日数より実際の滞船日数が長かった場合に契約者から船主に支払うレート）、ハッチ数、ハッチサイズ、及び積載可能量に関する情報が含まれている。また、船のサイズは、積載可能量によって異なり、小型（３万トン積載可能）、パナマクス（７〜９万トン積載可能）、ケープ（１５〜１７万トン積載可能）、及び大型（２３〜３０万トン積載可能）がある。また、船主との契約内容には、長期使用を前提とした専用船、都度契約し１回の航海で契約が終了するスポット船がある。また、揚げラン、デスレート、及びデマレートは、滞船料の計算時に必要となり、船毎に契約によって決められている。 The attribute information / motion information DB 2a is as shown in Table 1 below. The attribute information of the ship used for transporting the raw materials and the scheduled date when the ship is engaged in preparing the ship assignment plan and can depart for the next voyage Stores movement information indicating (next voyage possible date). Here, the ship attribute information includes the ship ID, the size required for considering whether or not to enter the berth, the details of the contract with the shipowner, the lifting run (the weight of the raw material that can be unloaded per day), the death rate ( The rate paid by the owner to the contractor if the actual number of days of stagnation is shorter than the planned number of days of stagnation), the demarcation (the rate of payment from the contractor to the owner if the number of days of actual stagnation is longer than the planned number of days of stagnation), Information about the number of hatches, hatch size, and loadable capacity is included. The size of the ship varies depending on the load capacity, and is small (capable of loading 30,000 tons), panamax (capable of loading 70 to 90,000 tons), cape (capable of loading 150 to 170,000 tons), and large (23 to 30). 10,000 tons can be loaded). Contracts with shipowners include special ships that are premised on long-term use, and spot ships that are contracted each time and the contract ends on a single voyage. In addition, the fried run, death rate, and demarcation are required when calculating the berthing fee and are determined by contract for each ship.
入港制約情報ＤＢ２ｂは、以下の表２に示すような、原料の積地及び揚地での船のバースへの入港可否制約に関する船の入港制約情報（入港不可船サイズ）及び積地での荷役日数（実績値の平均値）に関する情報を格納している。なお、揚地のデータには荷役日数は入らない。 As shown in Table 2 below, the port entry restriction information DB 2b is a port entry restriction information (ship entry unacceptable ship size) and cargo handling at the place of loading regarding raw material loading and unloading restrictions on a ship berth at a landing site. Stores information related to the number of days (average of actual values). In addition, the loading days are not included in the data of the landing site.
バース情報ＤＢ２ｃは、以下の表３に示すような、各揚地のバース情報（所属している地区名）及びバース毎の荷役能率に関する情報を格納している。 The berth information DB 2c stores berth information (name of district to which each berth belongs) and information on the cargo handling efficiency for each berth as shown in Table 3 below.
航海日数情報ＤＢ２ｄは、以下の表４に示すような、各積地と各揚地との間の航海日数に関する情報を格納している。 The sailing days information DB 2d stores information on the days of sailing between each loading place and each landing place as shown in Table 4 below.
各地区要求予定情報ＤＢ２ｅは、以下の表５に示すような、各地区で必要な原料の銘柄（銘柄名、銘柄区分名）とその量及び荷揚げ希望期間（荷揚げ開始日時、荷揚げ終了日時）を示した各地区要求予定情報を格納している。ここで、銘柄とは、成分、粘度、粒度等が異なる原料の名称を意味し、銘柄区分とは、石炭やコークス等の各原料の銘柄の総称を意味する。 Each district request schedule information DB 2e shows the brand name (brand name, brand category name) and quantity required for each district as shown in Table 5 below, and the desired unloading period (unloading start date / time, unloading end date / time). Each district request schedule information shown is stored. Here, the brand means names of raw materials having different components, viscosities, particle sizes, and the like, and the brand classification means a generic name of brands of raw materials such as coal and coke.
銘柄単位積載予定合計量情報ＤＢ２ｆは、以下の表６に示すような、計画期間の間に各積地で荷積みする原料の銘柄単位の予定数量を示した銘柄単位積載予定合計量に関する情報を格納している。 The brand unit planned total loading information DB 2f includes information on the total brand unit loading planned quantity indicating the planned quantity of the brand unit of the raw material to be loaded at each loading site during the planning period as shown in Table 6 below. Storing.
配船計画作成装置３は、パーソナルコンピュータやワークステーション等の情報処理装置によって構成され、属性情報・動静情報ＤＢ２ａ、入港制約情報ＤＢ２ｂ、バース情報ＤＢ２ｃ、航海日数情報ＤＢ２ｄ、各地区要求予定情報ＤＢ２ｅ、銘柄単位積載予定合計量情報ＤＢ２ｆ、及び配船計画ＤＢ４と電気的に接続されている。配船計画作成装置３は、情報処理装置内部の演算処理装置がコンピュータプログラムを実行することによって、配船計画最適化モデル作成部３ａ、最適化計算部３ｂ、銘柄区分内容決定モデル作成部３ｃ、及び銘柄区分内容決定計算部３ｄとして機能する。これら各部の機能については後述する。 The ship allocation plan creation device 3 is constituted by an information processing device such as a personal computer or a workstation, and includes an attribute information / motion information DB 2a, a port entry restriction information DB 2b, a berth information DB 2c, a voyage day information DB 2d, each district request schedule information DB 2e, It is electrically connected to the brand unit planned total loading amount information DB 2 f and the ship allocation plan DB 4. The ship allocation plan creation device 3 is configured such that a processing unit inside the information processing apparatus executes a computer program, thereby allowing a ship allocation plan optimization model creation unit 3a, an optimization calculation unit 3b, a brand category content determination model creation unit 3c, And it functions as the stock category content determination calculator 3d. The functions of these units will be described later.
配船計画ＤＢ４は、配線計画作成装置３によって作成された配船計画に関する情報を外部から閲覧可能な状態で格納している。 The ship assignment plan DB 4 stores information related to the ship assignment plan created by the wiring plan creation device 3 in a state where it can be viewed from the outside.
このような構成を有する配船計画作成システム１では、配船計画作成装置３が、以下に示す配船計画作成処理を実行することによって、原料の安定供給及び輸送コストの最小化を両立させた複数の積地から複数の揚地への配船計画を作成する。以下、図２に示すフローチャートを参照して、配船計画作成処理を実行する際の配船計画作成装置３の動作について説明する。 In the ship assignment plan creation system 1 having such a configuration, the ship assignment plan creation device 3 executes the following ship assignment plan creation processing, thereby achieving both stable supply of raw materials and minimization of transportation costs. Create a ship allocation plan from multiple loading sites to multiple landing sites. Hereinafter, with reference to the flowchart shown in FIG. 2, the operation of the ship allocation plan creation device 3 when executing the ship allocation plan creation processing will be described.
〔配船計画作成処理〕
図２は、本発明の一実施形態である配船計画作成処理の流れを示すフローチャートである。図３は、時空間ネットワークの一例を示す模式図である。図２に示すフローチャートは、配船計画作成装置３に対して配船計画作成処理の実行が指示されたタイミングで開始となり、配船計画作成処理はステップＳ１の処理に進む。
[Shipment planning process]
FIG. 2 is a flowchart showing the flow of a ship allocation plan creation process according to an embodiment of the present invention. FIG. 3 is a schematic diagram illustrating an example of a spatiotemporal network. The flowchart shown in FIG. 2 is started at the timing when execution of the ship assignment plan creation process is instructed to the ship assignment plan creation apparatus 3, and the ship assignment plan creation process proceeds to the process of step S1.
ステップＳ１の処理では、配船計画最適化モデル作成部３ａが、属性情報・動静情報ＤＢ２ａ、入港制約情報ＤＢ２ｂ、バース情報ＤＢ２ｃ、航海日数情報ＤＢ２ｄ、各地区要求予定情報ＤＢ２ｅ、及び銘柄単位積載予定合計量情報ＤＢ２ｆに格納されている情報を読み込む。また、配船計画最適化モデル作成部３ａは、銘柄単位積載予定合計量情報ＤＢ２ｆから読み込んだ銘柄単位積載予定合計量から銘柄区分単位の積載予定合計量を算出する。これにより、ステップＳ１の処理は完了し、配船計画作成処理はステップＳ２の処理に進む。 In the process of step S1, the ship allocation plan optimization model creation unit 3a performs the attribute information / movement information DB 2a, the port entry restriction information DB 2b, the berth information DB 2c, the voyage day information DB 2d, each district request schedule information DB 2e, and the brand unit loading schedule. The information stored in the total amount information DB 2f is read. Further, the ship allocation plan optimization model creation unit 3a calculates the total planned loading amount of the brand classification unit from the total brand unit loading planned total amount read from the brand unit planned loading total amount information DB 2f. Thereby, the process of step S1 is completed and a ship allocation plan preparation process progresses to the process of step S2.
ステップＳ２の処理では、配船計画最適化モデル作成部３ａが、銘柄区分単位の配船計画の最適化モデルを作成する。具体的には、配船計画最適化モデル作成部３ａは、以下の表７に示す離散的な時間（Ｔ１、Ｔ２、Ｔ３、Ｔ４、…）毎に各地点（積地及び揚地）に対応するノードｎを生成し、図３に示すようにノードｎ間の接続関係を表すパスｐを張った時空間ネットワークを船の数だけ作成する。多港積み及び多港揚を時空間ネットワークで表現することにより、多港積み及び多港揚げを数式で表現することができる。 In the process of step S2, the ship allocation plan optimization model creating unit 3a creates an optimization model for the ship allocation plan for each brand category. Specifically, the ship allocation plan optimization model creation unit 3a corresponds to each point (loading site and landing site) for each discrete time (T1, T2, T3, T4,...) Shown in Table 7 below. As shown in FIG. 3, a spatio-temporal network having a path p representing the connection relation between the nodes n is created as many as the number of ships. By expressing multi-port loading and multi-port unloading with a spatio-temporal network, multi-port loading and multi-port unloading can be expressed by mathematical expressions.
具体的には、ノードｎ間にパスｐを張る条件として、ノードｎが表す地点の属性が以下の表８に示す関係にあることに加え、ノードｎが表す地点間が表４に示した航海日数で移動可能な地点間である必要がある。なお、表８に示す"日本出発"や"航海終了"の各地点はネットワークを考慮するために便宜的に設けられたものであり、"日本出発"（揚地）から各積地への航海日数は表４に示した各地区から積地への航海日数の平均値とする。また、各地点から"航海終了"までの航海日数はゼロとする。さらに、ノードｎ間にパスｐを張る条件として、入港不可能な積地や揚地バースの地点を表すノードｎへはパスｐを張らないこととする。 Specifically, as a condition for establishing a path p between nodes n, the attributes of the points represented by node n are in the relationship shown in Table 8 below, and the navigation between the points represented by node n is shown in Table 4 It must be between points that can be moved in days. The “Japan departure” and “Navigation end” points shown in Table 8 are provided for convenience in consideration of the network. The number of days is the average value of the number of days of voyage from each area to the loading area shown in Table 4. In addition, the number of voyage days from each point to “end of voyage” is zero. Further, as a condition for establishing a path p between the nodes n, it is assumed that the path p is not extended to the node n representing a loading point or a landing berth point that cannot enter the port.
また、船ｓの集合をＳ、航海ｖの集合をＶ、ノードｎの集合をＮ、パスｐの集合をＰ、船ｓが航海ｖにおいてパスｐを通過する場合は１、パスｐを通過しない場合は０となる変数をｘｓｖｐ、ノードｎに入るパスｐの集合をＰｉｎ（ｎ）、ノードｎから出ていくパスｐの集合をＰｏｕｔ（ｎ）とすると、船の移動は以下に示す数式（１）のように表現することができる。 Also, the set of ships s is S, the set of voyages v is V, the set of nodes n is N, the set of paths p is P, 1 if the ship s passes the path p in the voyage v, and the path p is not passed. In this case, if x svp is a variable that becomes 0, a set of paths p entering node n is P in (n), and a set of paths p exiting node n is P out (n), the movement of the ship is It can be expressed as shown in Equation (1).
また、前航海から次航海へ向かう数式表現は、航海終了を表す地点のノードｎの集合をＮｖｅ、日本出発を表す地点のノード集合をＮｊｓとして、以下に示す数式（２）のように表現することができる。 Also, the mathematical expression from the previous voyage to the next voyage is expressed by the following equation (2), where N ve is a set of nodes n representing the end of the voyage and N js is a node set representing points departing from Japan. Can be expressed.
また、銘柄区分ｇの集合をＧ、船ｓが航海ｖにおいて銘柄区分ｇの原料をノードｎで荷揚げする量を決める変数をｗｓｖｎｇとすると、船の上限積載量ＳＣｓは以下に示す数式（３）のように表現することができる。ここで、数式（３）中、Ｎａは全揚地バースの地点を表すノード集合を示す。 Further, if the set of the brand classification g is G and the variable that determines the amount by which the ship s unloads the raw material of the brand classification g at the node n in the voyage v is w svng , the upper limit loading capacity SC s of the ship is expressed by the following formula ( It can be expressed as 3). Here, in the mathematical formula (3), Na indicates a node set representing the point of the all landing berth.
また、当然、積地に立ち寄らなければ荷揚げする原料は積載できないので、積地ｋの集合をＫ、積地ｋを表すノード集合をＮｋ、積地ｋで荷積みできる銘柄区分集合をＧｋとして、制約式は以下に示す数式（４）のように表現することができる。 Naturally, since the raw material to be unloaded cannot be loaded unless it stops at the loading site, the set of loading points k is K, the node set representing loading point k is Nk, and the brand classification set that can be loaded at loading point k is Gk. The constraint equation can be expressed as the following equation (4).
また、銘柄区分別の積載予定合計量以上の量は船に積載できないため、銘柄区分ｇ毎に決めた積地別積載予定合計量をＣＱｇとすると、制約式は以下に示す数式（５）のように表現することができる。 In addition, since the amount more than the planned total loading amount for each brand category cannot be loaded on the ship, if the total planned loading amount for each loading category determined for each brand category g is CQ g , the constraint equation is the following formula (5) It can be expressed as
また、原料を格納する船のハッチの数及びそのサイズは決まっており、同ハッチへは異なる銘柄の原料を入れることはできない（但し、ハッチ毎にサイズは同一であるとし、バッチの数とサイズとを掛け合わせた値はその船の積載可能量と等しいこととする）。このため、ハッチを考慮するため以下の数式（６）に示す制約式を設ける。ここで、数式（６）中、ｈａｔｃｈＵｓｅＧｓｖｇは船ｓが航海ｖで銘柄区分ｇの原料を入れるハッチ数を表す整数変数を示し、ＨａｔｃｈＳｉｚｅｓは１つのハッチのサイズを示す。 In addition, the number of hatches and the size of the ship's hatches that store raw materials are fixed, and different brands of raw materials cannot be put into the hatches (however, the size is the same for each hatch, and the number and size of batches are the same). The value multiplied by is equal to the ship's load capacity). For this reason, in order to consider a hatch, the constraint equation shown in the following equation (6) is provided. Here, in Equation (6), hatchUseG svg represents an integer variable representing the number of hatches in which the ship s enters the stock classification g in the voyage v, and HatchSize s represents the size of one hatch.
また、船ｓのハッチの数をＨａｔｃｈＮｕｍｂｅｒｓとすると、ハッチ数に関する制約式は以下に示す数式（７）のように表現することができる。 Further, if the number of hatches of the ship s is HatchNumber s , the constraint equation regarding the number of hatches can be expressed as the following formula (7).
また、荷揚げ量と荷揚げ能率を考慮した荷役作業時間分だけ、船が荷揚げバースに留まる必要があることの数式表現は、ノードｎに対応する単位時間当たりの荷揚能率をＵＣｎとして、以下に示す数式（８）のように表現することができる。但し、荷揚げバースと対応するノード集合Ｎａにのみ設けている。このように表現することにより、各ノードに荷役能率を設定することができるため、バースの荷揚げ設備の修理に伴う荷役能率の低下等を詳細に考慮することができる。 In addition, the mathematical expression that the ship needs to stay on the unloading berth for the handling work time in consideration of the unloading amount and the unloading efficiency is shown below with the unloading efficiency per unit time corresponding to the node n as UC n. It can be expressed as Equation (8). However, it is provided only in the node set Na corresponding to the unloading berth. By expressing in this way, it is possible to set the cargo handling efficiency for each node, and therefore, it is possible to consider in detail the reduction in cargo handling efficiency associated with the repair of the berth unloading equipment.
また、荷揚げバースには同時に１隻しか入れないことの数式表現は、ある荷揚げバースｂｅｒｔｈの集合をＢｅｒｔｈｓ、荷揚げバースｂｅｒｔｈのノード集合をＮｂｅｒｔｈとして、以下に示す数式（９）のように表現することができる。 Further, mathematical representation of that accommodate only one vessel simultaneously on the landing Bath, a set of some unloading berth berth Berths, the node set of unloading berth berth as N berth, expressed as Equation (9) below be able to.
また、荷揚げ量ｗｓｖｎｇは各地区で決められた要求予定を満たす必要があることの数式表現は、要求予定情報ｄの集合をＤ、要求している揚地の地区を含むノード集合をＮｄ、開始日をＳｔａｒｔＴｄ、終了日をＥｎｄＴｄ、要求予定情報ｄにおいて要求されている銘柄区分をｇｄ、量をＡｍｏｕｎｔｄ、ノードｎの時間をＴｎとして、以下に示す数式（１０）のように表現することができる。 Also, the mathematical expression that the unloading amount w svng needs to satisfy the required schedule determined in each district is expressed as follows: D is a set of requested schedule information d, and N d is a node set including the district of the requested landing site. , StartTd start date, EndTd an end date, gd stocks segment being requested in the request schedule information d, the amount of the amount d, the time of the node n as T n, expressed as equation (10) shown below can do.
以上の式により、ある地点から他の地点への移動に航海日数及び荷役時間を考慮する制約、船の積載可能量以上の積荷は積めないことを考慮する制約、及び各地区の要求予定を満たして船の積載内容を決める制約を考慮した、原料の安定供給のための船の運航ルート及び荷積みと荷揚げ内容を決めることができる。 By the above formula, the restriction considering the voyage time and the cargo handling time for moving from one point to another point, the restriction considering not loading more than the load capacity of the ship, and the required schedule of each district are satisfied. It is possible to determine the ship operation route and the loading and unloading contents for the stable supply of raw materials, taking into account the constraints that determine the loading contents of the ship.
また、上記制約を満たす計画の中から輸送コストの少ない計画を作成するために、評価基準として、スポット傭船費用最小化、滞船料最小化、及び多港揚げ/多港積み回数最小化を設ける。それぞれの定式化は下記のようになる。 In addition, in order to create a plan with a low transportation cost from among the plans that satisfy the above constraints, the spot dredger cost minimization, the berthing fee minimization, and the multi-port landing / multi-port loading frequency minimization will be established as evaluation criteria. . Each formulation is as follows.
スポット傭船費用の計算の際は、スポット船の集合をＳｓｐｏｔとし、実際に使役した航海回数を計算するため、１港目寄港の全積地ノード集合ＮＯ１のうちのいずれかのノードを通過した回数をカウントする。これにより、１回航海当たりの傭船費Ｃｏｓｔｓｐｏｔとして、スポット傭船費用ＳｐｏｔＣｏｓｔは以下に示す数式（１１）のように表現することができる。 The calculation of the spot chartered costs, a set of spots vessels and S spot, to calculate the voyage number of actual causative, pass through one of the nodes of the total Sekichi nodes 1 harbor first port of call set N O1 Count the number of times As a result, the spot chartering cost SpotCost can be expressed as the following formula (11) as the chartering cost Cost spot per one voyage.
また、船ｓの航海ｖの滞船料ＤｅｓＤｅｍｓｖは、船ｓのデスレートをＤｅｓｓ、デマレートをＤｅｍｓ、揚げランをＲｕｎｓ、各揚地の沖待ち地点及びバース地点の集合をＮｏｋｉ＆ｂｅｒｔｈとして、以下の数式（１２）に示す条件が成立する場合、以下に示す数式（１３）のように表現することができる。 In addition, demurrage DesDem sv voyage v of the ship s is, Des the Desureto of the ship s s, Demareto the Dem s, fried run Run s, a set of offshore waiting point and Bath point of each Yochi as N oki & berth When the condition shown in the following formula (12) is satisfied, it can be expressed as the following formula (13).
一方、以下の数式（１４）に示す条件が成立する場合には、船ｓの航海ｖの滞船料ＤｅｓＤｅｍｓｖは、以下に示す数式（１５）のように表現することができる。 On the other hand, when the condition shown in the following formula (14) is satisfied, the stagnation fee DesDem sv for the voyage v of the ship s can be expressed as the following formula (15).
多港揚げ／多港積み回数の最小化は、２港目寄港の全積地ノード集合をＮｏ２、２港目寄港の全揚地ノード集合をＮａ２とすると、寄港回数が１回増える毎にかかるコストＣｏｓｔｍｕｌｔｉＬｏａｄとして、以下に示す数式（１６）のように表現することができる。 Minimizing multi Harbor fried / multi Harbor stacking count, if all Sekichi set of nodes 2 harbor first port of call N o2, 2 all Yochi set of nodes harbor th boats and N a2, each is boats number increases once Cost Cost MultiLoad can be expressed as the following formula (16).
従って、以下の数式（１７）に示す評価関数を最小化することにより、輸送コストの少ない計画を作成することができる。これにより、ステップＳ２の処理は完了し、配船計画作成処理はステップＳ３の処理に進む。 Therefore, a plan with a low transportation cost can be created by minimizing the evaluation function shown in the following mathematical formula (17). Thereby, the process of step S2 is completed, and a ship allocation plan preparation process progresses to the process of step S3.
ステップＳ３の処理では、最適化計算部３ｂが、ステップＳ２の処理において作成された最適化モデルとステップＳ１の処理において読み込んだデータとを用いて混合整数線形計画法等の数理最適化を実施し、最適化モデルの変数の値を算出する。変数の値は表７中の通過するノード（通過地点とその地点を通過する時間）及び各地区への荷揚げ銘柄区分と荷揚げ量（荷積み量と同じ）を表している。このため、以下の表９に示すような銘柄区分単位（表９に示す例では銘柄区分名Ｇ１，Ｇ３，Ｇ４）の配船計画を作成できたことになる。これにより、ステップＳ３の処理は完了し、配船計画作成処理はステップＳ４の処理に進む。 In the process of step S3, the optimization calculation unit 3b performs mathematical optimization such as mixed integer linear programming using the optimization model created in the process of step S2 and the data read in the process of step S1. Calculate the value of the optimization model variable. The value of the variable represents the passing node (passing point and time passing through the point) in Table 7, the unloading brand classification and the unloading amount (same as the loading amount) to each area. For this reason, it is possible to create a ship allocation plan of brand classification units as shown in Table 9 below (brand classification names G1, G3, G4 in the example shown in Table 9). Thereby, the process of step S3 is completed, and a ship allocation plan preparation process progresses to the process of step S4.
ステップＳ４の処理では、銘柄区分内容決定モデル作成部３ｃが、ステップＳ３の処理において作成された銘柄区分単位の配船計画のデータ（最適化計算結果）を読み込む。これにより、ステップＳ４の処理は完了し、配船計画作成処理はステップＳ５の処理に進む。 In the process of step S4, the brand classification content determination model creation unit 3c reads the data (optimization calculation result) of the ship allocation plan for the brand classification created in the process of step S3. Thereby, the process of step S4 is completed, and a ship allocation plan preparation process progresses to the process of step S5.
ステップＳ５の処理では、銘柄区分内容決定モデル作成部３ｃが、ステップＳ４の処理において読み込まれたデータを用いて実操業に必要な銘柄単位での船への荷積み量及び荷揚げ量（銘柄区分内容）を決定するモデルを作成する。具体的には、銘柄ｍの集合をＭ、銘柄単位の船ｓの航海ｖにおけるノードｎでの銘柄ｍの荷揚げ量を表す変数をｗＤｓｖｎｍとすると、銘柄単位で積地別積載予定合計量を考慮した銘柄単位での荷揚げ量は、銘柄ｍの積載予定量合計をＣＱＤｍとして、以下に示す数式（１８）のように表現することができる。 In the process of step S5, the brand classification content determination model creation unit 3c uses the data read in the process of step S4 to load and unload the ship into the ship in units of brands necessary for actual operation (brand classification content). Create a model that determines). Specifically, if the set of brands M is M, and the variable representing the amount of brand m unloaded at node n in the voyage v of the ship s in brand units is wD svnm , The amount of unloading in consideration of the brand unit can be expressed as the following formula (18), where CQD m is the total loading amount of the brand m.
また、ステップＳ３の処理で求めた銘柄区分単位での船ｓの航海ｖにおけるノードｎでの銘柄区分ｇの荷揚げ量をＷｓｖｎｇ、地区ｃが保有するバースを示す地点のノード集合をＮｃ、銘柄区分ｇに属する銘柄ｍの集合をＭｇとすると、ステップＳ３の処理において決めた配船計画に則り、銘柄単位での荷揚げする地区での荷揚げ量を決定する数式は、以下に示す数式（１９）のように表現することができる。 Also, W svng is the unloading amount of the brand classification g at the node n in the voyage v of the ship s in the brand classification unit obtained in the processing of the step S3, Nc is the node set of points indicating the berths held by the district c, and the brand Assuming that the set of brands m belonging to category g is Mg, the mathematical formula for determining the amount of unloading in the district where the brand is unloaded in accordance with the ship allocation plan determined in the processing of step S3 is the following mathematical formula (19): It can be expressed as
また、ステップＳ２の処理と同様、ハッチのサイズ及びハッチ数を考慮する必要があるため、船ｓの航海ｖで銘柄ｍを入れるハッチ数を表す整数変数をｈａｔｃｈＵｓｅｓｖｍ、１つのハッチのサイズをＨａｔｃｈＳｉｚｅｓとして、ハッチサイズの制約式は以下に示す数式（２０）のように表現することができる。 Similarly to the processing of step S2, since it is necessary to consider the size of the hatch and the number of hatches, an integer variable representing the number of hatches into which the brand m is inserted in the voyage v of the ship s is hatchUse svm , and the size of one hatch is HatchSize. As s , the hatch size constraint equation can be expressed as the following equation (20).
また、船ｓのハッチの数をＨａｔｃｈＮｕｍｂｅｒｓとすると、ハッチ数の制約式は以下に示す数式（２１）のように表現することができる。 Further, if the number of hatches of the ship s is HatchNumber s , the constraint formula for the number of hatches can be expressed as the following formula (21).
以上の制約式を制約とし、これら条件を満たす変数ｗＤｓｖｎｍの組合せの中から最適なものを決定する評価基準として、１回の航海では可能な限り複数の銘柄を運ぶことを考える。この評価基準は、ハッチの使用数ｈａｔｃｈＵｓｅｓｖｍの最小値を評価関数とし、その評価関数を最大化することになるため、以下に示す数式（２２）のように表現することができる。これにより、ステップＳ５の処理は完了し、配船計画作成処理はステップＳ６の処理に進む。 Considering the above constraint formula as a constraint, and as an evaluation criterion for determining the optimum one from the combinations of variables wD svnm that satisfy these conditions, it is considered that a single voyage carries as many brands as possible. Since this evaluation criterion uses the minimum value of the hatch usage number hatchUse svm as an evaluation function and maximizes the evaluation function, it can be expressed as the following formula (22). Thereby, the process of step S5 is completed, and a ship allocation plan preparation process progresses to the process of step S6.
ステップＳ６の処理では、銘柄区分内容決定計算部３ｄが、ステップＳ５の処理において作成された最適化モデルとステップＳ１及びステップＳ４の処理において読み込まれたデータとを用いて混合整数線形計画法等の数理最適化を実施し、最適化モデルの変数の値を算出する。これにより、銘柄区分単位であった荷積み／荷揚げ内容が銘柄単位で決定され、以下の表１０に示す銘柄単位（表１０に示す例では銘柄名Ｍ１，Ｍ２，Ｍ３，Ｍ４）での配船計画が作成される。ここで、原料の各銘柄と荷積みできる積地は１対１対応しているため、荷揚げ内容が決まれば、荷積み内容も一意に決まる。そして、配船計画作成装置３は、作成された配船計画のデータを配船計画ＤＢ４内に格納する。以後、製鉄所では、作成された配船計画に基づいて輸送されてきた原料を用いて鉄鋼製品を生産する。これにより、ステップＳ６の処理は完了し、一連の配船計画作成処理は終了する。 In the process of step S6, the brand category content determination calculation unit 3d uses the optimization model created in the process of step S5 and the data read in the processes of step S1 and step S4 to perform mixed integer linear programming or the like. Mathematical optimization is performed, and the value of the optimization model variable is calculated. As a result, the loading / unloading contents, which were the brand division unit, are determined by the brand unit, and the dispatch in the brand unit shown in Table 10 below (brand names M1, M2, M3, and M4 in the example shown in Table 10). A plan is created. Here, since the loading place that can be loaded with each brand of the raw material has a one-to-one correspondence, if the contents of unloading are determined, the contents of loading are also uniquely determined. The ship assignment plan creation device 3 stores the created ship assignment plan data in the ship assignment plan DB 4. Thereafter, steelworks produce steel products using raw materials that have been transported based on the prepared ship allocation plan. Thereby, the process of step S6 is completed and a series of ship allocation plan preparation processes are complete | finished.
以上の説明から明らかなように、本発明の一実施形態である配船計画作成処理によれば、配船計画作成装置３が、少なくとも船の属性情報及び動静情報、各積地と各揚地との間の航海日数、地区要求予定情報、計画期間の間における各積地での銘柄単位積載予定合計量の情報を読み込み、ある地点から他の地点への移動に航海日数及び荷役時間を考慮する制約、船の積載可能量を考慮する制約、及び各地区の要求予定を満たして船の積載内容及び荷揚内容を決める制約を含めた制約とし、少なくとも滞船料コストを評価関数とし、この制約及び評価関数を数式で表し、評価関数を最小化する最適化モデルを作成し、制約に従って最適化モデルを数理最適化手法により解くことによって配船計画を作成する。これにより、原料の安定供給及び輸送コストの最小化を両立させた複数の積地から複数の揚地への配船計画を作成することができる。また、作成された配船計画に基づいて輸送されてきた原料を用いて鉄鋼製品を生産することにより、高品質な鉄鋼製品を安定的に、且つ、低コストで生産することができる。 As is clear from the above description, according to the ship allocation plan creation processing according to an embodiment of the present invention, the ship allocation plan creation device 3 includes at least ship attribute information and movement information, each loading place and each landing place. Voyage days, district request schedule information, and information on the planned total loading amount of each brand at each loading point during the planning period, taking into account voyage days and cargo handling time when moving from one point to another And restrictions that consider the load capacity of the ship, and restrictions that determine the contents of loading and unloading of the ship by satisfying the requirements of each region, and at least the stagnation fee cost as an evaluation function. The evaluation function is expressed by a mathematical expression, an optimization model that minimizes the evaluation function is created, and a ship allocation plan is created by solving the optimization model by a mathematical optimization method according to the constraints. As a result, it is possible to create a ship allocation plan from a plurality of loading sites to a plurality of landing sites that achieves both stable supply of raw materials and minimization of transportation costs. Moreover, by producing steel products using raw materials that have been transported based on the created ship allocation plan, high-quality steel products can be produced stably and at low cost.
また、本発明の一実施形態である配船計画作成処理によれば、データ読み込みステップは、原料の銘柄のグルーピングを設定した銘柄区分情報を読み込み、銘柄単位積載予定合計量の情報から銘柄区分毎に集約した銘柄区分単位積載予定合計量の情報を作成するステップを含み、最適化モデル作成ステップは、銘柄区分単位積載予定合計量の情報を用いて銘柄区分単位の最適化モデルを作成するステップと、銘柄区分単位の最適化モデルを解くことによって得られる銘柄区分単位の荷積み量及び荷揚げ量を用いて銘柄単位での荷積み量及び荷揚げ量を決定する銘柄区分内容決定モデルを作成するステップと、を含み、最適化モデル計算ステップは、銘柄区分単位の最適化モデルを解いた後に銘柄区分内容決定モデルを解くステップを含む。すなわち、本発明の一実施形態である配船計画作成処理では、銘柄区分単位で配船計画を決定した後に銘柄区分の内容を（銘柄単位での荷積み量及び荷揚げ量）を決定している。これにより、最適化問題を分割して解くことができるので、計算時間を短縮することができる。 Further, according to the ship allocation plan creation processing according to an embodiment of the present invention, the data reading step reads the brand classification information in which the brand grouping of the raw material is set, and determines each brand classification from the information of the total planned loading amount of the brand unit. The optimization model creation step includes a step of creating an optimization model of the stock classification unit using the information of the stock category unit scheduled total loading. Creating a brand classification content determination model for determining the loading and unloading amount in each brand unit using the loading and unloading quantity in the brand classification unit obtained by solving the optimization model of the brand classification unit; The optimization model calculation step includes a step of solving the brand classification content determination model after solving the optimization model of the brand division unit. That is, in the ship allocation plan creation process according to an embodiment of the present invention, after determining a ship allocation plan for each brand category, the contents of the brand category (the loading amount and the unloading amount for each brand unit) are determined. . Thereby, since the optimization problem can be divided and solved, the calculation time can be shortened.
なお、各地区の要求予定を満たす制約について、以下に示すように制約と評価関数を変更し、要求の重要度に合わせて輸送コストとのバランスを考慮させてもよい。具体的には、この場合、要求予定情報ｄの要求量Ａｍｏｕｎｔｄを満たせなかった分量をＳｈｏｒｔａｇｅＡｍｏｕｎｔｄとして、以下に示す数式（２３）に変更し、要求予定情報ｄ毎の重要度を表す情報を追加で読み込み、以下の数式（２４）に示すように満たせなかった分量に重みＳｈｏｒｔａｇｅＷｄ（値は重要度）を掛けた合計を評価関数に足し合わせてもよい。 In addition, about the restrictions which satisfy | fill the request | requirement schedule of each district, a constraint and an evaluation function may be changed as shown below, and the balance with a transportation cost may be considered according to the importance of a request | requirement. Specifically, in this case, the amount that did not satisfy the request amount Amount d of the request schedule information d is changed to the formula (23) shown below as ShortageAmount d , and information indicating the importance for each request schedule information d is changed. Additional reading may be performed, and the sum obtained by multiplying the unsatisfied amount by the weight ShortageW d (value is importance) may be added to the evaluation function as shown in the following formula (24).
時間単位６０分で本発明により配船計画を作成した例を図４に示す。図４は、本発明により作成された配船計画の一例を示す図である。図４に示すように、多港積み及び多港揚げを考慮した配船計画が作成できていることがわかる。具体的には、船Ａについては、日本を出発した後、積地２において原料を積載し、２時間沖待ちし、揚地１のバース１で荷揚げし、１時間沖待ちし、揚地２のバース４で荷揚げする多港揚げの配船計画が作成されている。これにより、本発明によれば、原料の安定供給及び輸送コストの最小化を両立させた複数の積地から複数の揚地への配船計画を作成できることが確認された。 FIG. 4 shows an example of creating a ship allocation plan according to the present invention in 60 minutes. FIG. 4 is a diagram showing an example of a ship allocation plan created according to the present invention. As shown in FIG. 4, it can be seen that a ship allocation plan that considers multi-port loading and multi-port unloading has been created. Specifically, after leaving Japan, Ship A is loaded with raw materials at loading site 2, waits for two hours offshore, unloads at berth 1 at landing site 1, waits for one hour offshore, A multi-port unloading plan for unloading at berth 4 has been created. Thus, according to the present invention, it was confirmed that it is possible to create a ship allocation plan from a plurality of loading sites to a plurality of landing sites that achieve both stable supply of raw materials and minimization of transportation costs.
以上、本発明者らによってなされた発明を適用した実施形態について説明したが、本実施形態による本発明の開示の一部をなす記述及び図面により本発明は限定されることはない。例えば、このように、本実施形態に基づいて当業者等によりなされる他の実施形態、実施例、及び運用技術等は全て本発明の範疇に含まれる。 As mentioned above, although the embodiment to which the invention made by the present inventors was applied has been described, the present invention is not limited by the description and the drawings that constitute a part of the disclosure of the present invention according to this embodiment. For example, as described above, other embodiments, examples, operation techniques, and the like made by those skilled in the art based on the present embodiment are all included in the scope of the present invention.
１ 配船計画作成システム
２ａ 属性情報・動静情報ＤＢ
２ｂ 入港制約情報ＤＢ
２ｃ バース情報ＤＢ
２ｄ 航海日数情報ＤＢ
２ｅ 各地区要求予定情報ＤＢ
２ｆ 銘柄単位積載予定合計量情報ＤＢ
３ 配船計画作成装置
３ａ 配船計画最適化モデル作成部
３ｂ 最適化計算部
３ｃ 銘柄区分内容決定モデル作成部
３ｄ 銘柄区分内容決定計算部
４ 配船計画ＤＢ
1 Ship allocation plan creation system 2a Attribute information and movement information DB
2b Entry restriction information DB
2c Berth information DB
2d Sailing Days Information DB
2e Each district request schedule information DB
2f Total stock information DB for each brand
3 Ship allocation plan creation device 3a Ship allocation plan optimization model creation unit 3b Optimization calculation unit 3c Brand category content determination model creation unit 3d Brand category content determination calculation unit 4 Ship allocation plan DB
Claims (5)
コンピュータが備えるデータ読み込み部が、少なくとも前記船の属性情報及び動静情報、各積地と各揚地との間の航海日数、地区要求予定情報、計画期間の間における各積地での銘柄単位積載予定合計量の情報を読み込むデータ読み込みステップと、
コンピュータが備える最適化モデル作成部が、ある地点から他の地点への移動に航海日数及び荷役時間を考慮する制約、船の積載可能量を考慮する制約、及び各地区の要求予定を満たして船の積載内容及び荷揚内容を決める制約を含めた制約とし、少なくとも滞船料コストを評価関数とし、前記制約と前記評価関数を数式で表し、該評価関数を最小化する最適化モデルを作成する最適化モデル作成ステップと、
コンピュータが備える最適化モデル計算部が、前記制約に従って前記最適化モデルを数理最適化手法により解くことによって配船計画を作成する最適化モデル計算ステップと、
を含むことを特徴とする配船計画作成方法。 In a ship allocation plan creation device constructed using a computer, the computer creates a ship allocation plan for transporting various raw materials necessary for product production from multiple loading points to multiple landing sites by ship. A method,
The data reading unit of the computer has at least the attribute information and movement information of the ship, the number of days of voyage between each loading place and each landing place, the district request schedule information, and the brand unit loading at each loading place during the planning period A data reading step for reading information on the planned total amount,
The optimization model creation unit included in the computer satisfies the constraints that consider the number of voyage days and cargo handling time for moving from one point to another point, the constraints that consider the load capacity of the ship, and the requirements of each region. Optimizing to create an optimization model that minimizes the evaluation function, including constraints that determine the loading and unloading content of the ship, including at least the stagnation fee cost as an evaluation function, expressing the constraint and the evaluation function as mathematical expressions Modeling step,
An optimization model calculation step provided in a computer, an optimization model calculation step of creating a ship allocation plan by solving the optimization model according to the constraints by a mathematical optimization method;
A ship allocation plan creation method characterized by including:
前記最適化モデル作成ステップは、コンピュータが備える最適化モデル作成部が、銘柄区分単位積載予定合計量の情報を用いて銘柄区分単位の最適化モデルを作成するステップと、コンピュータが備える最適化モデル作成部が、銘柄区分単位の最適化モデルを解くことによって得られる銘柄区分単位の荷積み量及び荷揚げ量を用いて銘柄単位での荷積み量及び荷揚げ量を決定する銘柄区分内容決定モデルを作成するステップと、を含み、
前記最適化モデル計算ステップは、コンピュータが備える最適化モデル計算部が、銘柄区分単位の最適化モデルを解いた後に前記銘柄区分内容決定モデルを解くステップを含む
ことを特徴とする請求項１〜３のうち、いずれか１項に記載の配船計画作成方法。 In the data reading step, the data reading unit provided in the computer reads the stock classification information in which the stock brand groupings are set, and sums up the stock classification unit loading planned total amount for each stock classification from the information of the stock unit loading planned total amount Including the step of creating information for
The optimization model creation step includes a step in which an optimization model creation unit provided in the computer creates an optimization model for each brand category using information on the total planned loading amount of each brand category unit, and an optimization model creation provided in the computer Create a stock category content determination model that determines the loading and unloading amount for each brand using the loading and unloading amount of the stock classification unit obtained by solving the optimization model for the stock classification unit And including steps,
The optimization model calculation step includes a step in which an optimization model calculation unit provided in a computer solves the brand classification content determination model after solving the optimization model of the brand classification unit. Of these, the ship allocation plan creation method according to any one of the above.
少なくとも前記船の属性情報及び動静情報、各積地と各揚地との間の航海日数、地区要求予定情報、計画期間の間における各積地での銘柄単位積載予定合計量の情報を読み込むデータ読み込み部と、
ある地点から他の地点への移動に航海日数及び荷役時間を考慮する制約、船の積載可能量を考慮する制約、及び各地区の要求予定を満たして船の積載内容及び荷揚内容を決める制約を含めた制約とし、少なくとも滞船料コストを評価関数とし、前記制約と前記評価関数を数式で表し、該評価関数を最小化する最適化モデルを作成する最適化モデル作成部と、
前記制約に従って前記最適化モデルを数理最適化手法により解くことによって配船計画を作成する最適化モデル計算部と、
を備えることを特徴とする配船計画作成装置。 A ship assignment plan creation device for creating a ship assignment plan constructed by using a computer and transporting various raw materials necessary for product production from a plurality of loading sites to a plurality of landing sites,
Data that reads at least the attribute information and movement information of the ship, the number of days of voyage between each loading site and each landing site, the district request schedule information, and the information on the total planned loading amount of each brand at each loading site during the planning period A reading section;
Constraints that consider the number of days of voyage and cargo handling time when moving from one point to another, constraints that consider the load capacity of the ship, and constraints that determine the contents of loading and unloading of the ship that meet the requirements of each region An optimization model creation unit that creates an optimization model that minimizes the evaluation function, including the constraint, including at least a berthing fee cost as an evaluation function, expressing the constraint and the evaluation function by a mathematical expression,
An optimization model calculation unit that creates a ship assignment plan by solving the optimization model according to the constraints by a mathematical optimization method;
A ship allocation plan creation device characterized by comprising:
Priority Applications (1)
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| JP7175839B2 (en) | 2019-04-24 | 2022-11-21 | 株式会社日立製作所 | Transportation planning device, transportation planning system, and transportation planning method |
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| WO2022024679A1 (en) * | 2020-07-31 | 2022-02-03 | Ｊｆｅスチール株式会社 | Ship allocation plan formulation method, and operation method and ship allocation plan formulation device that are based on said ship allocation plan formulation method |
| CN113240234B (en) * | 2021-04-02 | 2024-01-12 | 大连海事大学 | Coordination and optimization method for coal port shipping equipment allocation and ship traffic organization |
| WO2025204340A1 (en) * | 2024-03-28 | 2025-10-02 | Ｅｎｅｏｓ株式会社 | Ship allocation plan creation device, ship allocation plan creation method, and recording medium |
| JP2025151422A (en) * | 2024-03-28 | 2025-10-09 | Ｅｎｅｏｓ株式会社 | Ship routing plan creation device, ship routing plan creation method, and ship routing plan creation program |
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