JP6848624B2 - Shipage estimation device, method and program - Google Patents

Description

The present invention is a ship stagnation estimation device suitable for use in obtaining an index regarding stagnation when delivering raw materials, materials, products, commodities, etc. to factories, commercial facilities, inventory bases, etc. using a ship. Regarding methods and programs.

In the industrial and commercial fields that handle a large amount of raw materials, materials, products, commodities, etc., factories, commercial facilities, and inventory are used as means of transportation in order to reduce transportation costs or to transport from overseas. It is delivered to bases, etc.
For example, steel makers, chemical makers, oil makers, etc. use large vessels to produce iron ore, coal, oil, gas, etc. from overseas production bases (regions such as Australia, Brazil, and the United States) in Japan. Transport to factories, commercial facilities, inventory bases, etc.

Here, as the transportation cost when using a ship, in addition to the cost of hiring a ship, a ship stagnation fee, which is a cost incurred according to the stagnation of the ship and the amount of transportation, is incurred. A ship stalled is a state of waiting other than when unloading.
Ship stagnation occurs for the following reasons. For example, it is necessary to berth in order to unload from a ship, but since the number of quays is limited, if a large number of ships arrive at one time, it may not be possible to berth immediately, which causes a stagnation. In addition, after the ship berths, the loaded goods will be unloaded, but the unloading time will increase according to the amount of goods to be unloaded, so the goods to be unloaded. Even if the amount is too large compared to the unloading capacity, the next vessel will be kept waiting, which will cause a stagnation. Furthermore, when public facilities are used as transportation facilities such as ports and railroads for shipping, and because shipping is carried out to multiple companies, various economic conditions such as priority between companies arise depending on the transaction status with each company. In such a case, it often happens that the ship is not shipped as scheduled and fluctuates significantly, which causes a stagnation. In addition, ships often make a round trip between the shipping source and factories, commercial facilities, inventory bases, etc., and once the operation cannot be performed as planned, the effect may spread to the future, and the ship arrives. It fluctuates significantly from the schedule and causes a stagnation.

In order to eliminate the stagnation, it is conceivable to optimize the amount of goods or increase the unloading capacity. However, optimizing the amount of goods also affects how to hold inventory and the size of ships, and a large investment is required to increase the unloading capacity. Therefore, it is important to estimate, for example, a ship stagnation fee as an index for stagnation, and to consider appropriate measures to reduce the stagnation fee.

Japanese Unexamined Patent Publication No. 2008-105825

"Introduction to Probabilistic Models" (written by Shunji Osaki) (May 1996, First Edition, Asakura Shoten)

Patent Document 1 describes a ship allocation plan planning device for formulating a long-term raw material transportation and distribution plan, a ship allocation plan adjustment device for creating a short-term raw material transportation and distribution plan, and a raw material transportation and distribution plan for each factory. The cargo handling adjustment device for each factory is equipped with a cargo handling adjustment device for each factory, and the cargo handling adjustment device for each factory amends the raw material transportation and allocation plan for each factory based on the short-term raw material transportation and allocation plan, and the ship allocation plan adjustment device is modified for each factory. A raw material transportation and distribution planning system and a raw material distribution planning method for modifying a short-term raw material transportation and distribution plan based on the raw material transportation and distribution plan and repeating these processes to formulate a short-term raw material distribution plan are disclosed. There is.

Further, Non-Patent Document 1 discloses the queuing theory, and the average waiting time is obtained from the number of customers arriving in a unit time (arrival rate) and the number of customers processed in a unit time (processing rate). It has been shown to be.

Patent Document 1 discloses that an early departure fee for each ship and a arrears fee when the scheduled period is exceeded are calculated based on the ship allocation schedule. However, in one case of a specific specific ship allocation schedule, that is, in a certain section, the berth fee is only calculated based on the ship allocation schedule given to that one section, and the target is It is not a calculation of the statistical tendency of the delinquency charge from the tendency of ship allocation and unloading capacity of the port. For example, if one month has passed and the ship allocation schedule is set ahead of the ship allocation schedule, the inventory amount for each brand in the yard will differ significantly, and the ship allocation schedule will be completely different from the previous ship allocation schedule. However, it was not considered in consideration of such a changing case. It is possible to calculate the arrears statistically by giving a ship allocation schedule every day and repeating the above processing, but it is not only a huge amount of labor, but also all statistical data. It is hard to say that the situation was taken into consideration.

Further, in the queuing theory shown in Non-Patent Document 1, the attributes possessed by the customer are not examined, and the arrival rate and the processing rate are independently examined. However, in the case of transportation by ship, in order to stably operate at factories, commercial facilities, inventory bases, etc., it is assumed that a certain amount will be transported for a certain period of time, and the amount of unloading, which is an attribute of ships, will be The larger the amount, the larger the amount transported at one time, so the arrival rate of the ship is small, and conversely, the smaller the amount of unloading, the larger the arrival rate of the ship. On the other hand, the larger the unloading amount, the longer the loading and unloading time, and conversely, the smaller the unloading amount, the shorter the loading and unloading time. In this way, there is a correlation between the arrival rate and the unloading amount, and the unloading amount and the processing rate, and therefore there is also a correlation between the arrival rate and the processing rate. Non-Patent Document 1 does not discuss this correlation. In addition, queuing theory requires the average waiting time per customer and the average waiting length, but for a certain period of time, such as months and years, which is necessary when considering costs in corporate activities. The total waiting time and costs incurred have not been considered.

The present invention has been made in view of the above points, and in applying the queuing theory, an index relating to a ship stagnation for a certain period of time is obtained in consideration of the correlation between the arrival rate and the processing rate. The purpose is to be able to.

The gist of the present invention for solving the above problems is as follows.
[1] A ship stagnation estimation device that obtains an index related to stagnation when delivering the target goods to the delivery destination using a ship.
An input means for importing actual information including the arrival date and time, berthing date and time, and departure date and time of each ship at the delivery destination from the database.
Based on the arrival date and time of the record information, which is number of vessels of vessel vessels distribution arrival interval in the delivery destination calculated according to a predetermined first probability density function, to arrive in per unit time in the delivery destination vessels The first distribution calculation means for calculating the arrival rate λ and
Based on the berthing date and time and the berthing date and time of the actual information, the distribution of cargo handling time, which is the time required for unloading per ship at the delivery destination, is calculated according to a predetermined second probability density function , and per ship. The average value α of the cargo handling time, the standard deviation σ of the cargo handling time per ship, and the second distribution calculation means for calculating the ship processing rate (= 1 / α) μ at the delivery destination.
The ship arrival rate λ, which is a parameter representing the distribution of the arrival intervals of ships calculated by the first distribution calculation means, and the parameter representing the distribution of cargo handling time per ship calculated by the second distribution calculation means. By substituting the mean value α, the standard deviation σ, and the ship processing rate μ into the equation of the queue theory , the ship stagnation time W per ship at the delivery destination is calculated for each ship. Ship time calculation means and
An index calculation means for calculating the stagnation time generated at the delivery destination for a certain period of time based on the stagnation time W per ship calculated by the stagnation time calculation means for each ship .
It is provided with an output means for outputting the berthing time generated at the delivery destination obtained by the index calculation means.
The index calculation means is a ship detention estimation device characterized in that the total amount of unloading in a certain period is treated as constant.
[2] The formula of the queuing theory is
W = {λ / (μ ・ (μ−λ))} ・ {(1+ (σ / α) ² ) / 2}
The ship stagnation estimation device according to [1].
[3] The index calculation means covers the fixed period, the relationship between the unloading amount per ship and the staying time per ship, and the unloading amount per ship and per day. The ship stagnation estimation device according to [1] or [2] , wherein the relationship with the stagnation time is obtained.
[4] The index calculation means obtains the relationship between the amount of unloading per vessel and the daily charge for a certain period of time by using the information on the charge for the charge per unit time. The ship stagnation estimation device according to [ 3].
[5] The ship stagnation estimation device according to [4 ], wherein the information on the stagnation fee per unit time is set for each ship type.
[6] The index calculation means calculates the total unloading amount as the number of ships arriving per day at the delivery destination, which is obtained from the distribution of the arrival intervals of the ships calculated by the first distribution calculation means. The ship detention estimation device according to any one of [1] to [5 ], which is represented by using the amount of unloading per ship.
[7] The index calculation means is a value obtained by subtracting the actual unloading time including at least one of the port entry preparation time and the setup time from the time required from the berthing to the berthing of the ship per ship. The ship arrears estimation device according to any one of [1] to [ 6 ], which comprises the cargo handling time of.
[8] The ship detention estimation device according to [7 ], wherein the actual unloading outside time is a constant.
[9] This is a method of estimating ship stagnation that obtains an index related to stagnation when delivering the target goods to the delivery destination using a ship.
The input means is an input procedure for fetching the actual information including the arrival date / time, berthing date / time, and departure date / time of each ship at the delivery destination from the database.
The first distribution calculation means calculates the distribution of the arrival interval of the ship at the delivery destination according to a predetermined first probability density function based on the arrival date and time of the actual information , and per unit date and time at the delivery destination. The first distribution calculation procedure for calculating the ship arrival rate λ, which is the number of arriving ships,
The cargo handling time, which is the time required for the second distribution calculation means to unload one vessel at the delivery destination according to a predetermined second probability density function based on the berthing date and time and the berthing date and time of the actual information. Second distribution calculation that calculates the distribution and calculates the average value α of the cargo handling time per ship α, the standard deviation σ of the cargo handling time per ship, and the ship processing rate (= 1 / α) μ at the delivery destination. Procedure and
The ship arrival time calculation means for each ship has the ship arrival rate λ, which is a parameter representing the distribution of the arrival intervals of the ships calculated in the first distribution calculation procedure, and one ship calculated in the second distribution calculation procedure. By substituting the average value α, the standard deviation σ, and the ship processing rate μ, which are parameters representing the distribution of cargo handling time per ship, into the equation of the queue theory, the stagnation per ship at the delivery destination The procedure for calculating the arrears time for each ship to calculate the ship time W,
An index calculation procedure for calculating the stagnation time generated at the delivery destination for a certain period of time based on the stagnation time W per ship calculated by the index calculation means for each ship stagnation time calculation procedure, and an index calculation procedure.
The output means has an output procedure for outputting the berthing time generated at the delivery destination obtained by the index calculation procedure .
The index calculation procedure is a method for estimating a ship stagnation, which comprises treating the total amount of unloading in a certain period as a constant.
[10] This is a program for obtaining an index related to arrears when delivering the target goods to the delivery destination using a ship.
An input means for importing actual information including the arrival date and time, berthing date and time, and departure date and time of each ship at the delivery destination from the database.
Based on the arrival date and time of the record information, which is number of vessels of vessel vessels distribution arrival interval in the delivery destination calculated according to a predetermined first probability density function, to arrive in per unit time in the delivery destination vessels The first distribution calculation means for calculating the arrival rate λ and
Based on the berthing date and time and the berthing date and time of the actual information, the distribution of cargo handling time, which is the time required for unloading per ship at the delivery destination, is calculated according to a predetermined second probability density function , and per ship. The average value α of the cargo handling time, the standard deviation σ of the cargo handling time per ship, and the second distribution calculation means for calculating the ship processing rate (= 1 / α) μ at the delivery destination.
The ship arrival rate λ, which is a parameter representing the distribution of the arrival intervals of ships calculated by the first distribution calculation means, and the parameter representing the distribution of cargo handling time per ship calculated by the second distribution calculation means. By substituting the mean value α, the standard deviation σ, and the ship processing rate μ into the equation of the queue theory , the ship stagnation time W per ship at the delivery destination is calculated for each ship. Ship time calculation means and
An index calculation means for calculating the stagnation time generated at the delivery destination for a certain period of time based on the stagnation time W per ship calculated by the stagnation time calculation means for each ship .
The computer is made to function as an output means for outputting the arrears time generated at the delivery destination obtained by the index calculation means.
The index calculation means is a program characterized in that the total amount of unloading in the fixed period is treated as constant.

According to the present invention, the arrival rate and the arrival rate when applying the queuing theory by grasping the tendency of the arrival interval of ships at the delivery destination and the time required for unloading per ship based on the actual information. Considering the correlation of the processing rate, it is possible to obtain the queuing time and the queuing fee generated at the delivery destination for a certain period of time.

It is a figure which shows the functional structure of the ship stoppage estimation device which concerns on embodiment. It is a flowchart which shows the ship stagnation estimation method by the ship stagnation estimation device which concerns on embodiment. It is a characteristic diagram which shows an example of the frequency distribution of the arrival interval of a ship. It is a characteristic diagram which shows an example of the frequency distribution of cargo handling time per ship. It is a characteristic diagram which shows the relationship between the unloading amount per ship and the staying time. It is a characteristic diagram which shows the relationship between the unloading amount per ship and the arrears fee per day.

Hereinafter, preferred embodiments of the present invention will be described with reference to the accompanying drawings.
In the present embodiment, a case where a steel raw material such as iron ore or coal is transported as a target article from overseas by using a ship will be described.
There are many countries that produce iron ore and coal, such as Australia, Brazil, and the United States, and each producing country also has multiple production bases. In Australia, it takes about 1.5 months in Brazil compared to arriving in Japan in about 1 to 2 weeks after leaving the port, and there is a big difference in the lead time. In addition, since there are many steel makers regardless of domestic, the ports on the producing country side are frequently affected by other companies such as delays in departure of other companies' ships when ships for multiple steel makers are shipped. Fluctuations in the departure schedule of vessels are large.
In this way, there is a large difference in lead time due to differences in producing countries, and while there are large fluctuations in departure schedules on the producing countries side, stable operations are carried out at delivery destinations (factories, commercial facilities, inventory bases, etc.). In addition, operations will be carried out so that fluctuations in unloading amount and daily usage amount can be kept small.
Therefore, paying attention to the fact that the daily fluctuation of the usage amount is not large, the total amount of the target goods to be unloaded (hereinafter referred to as the total amount of unloading) is constant when considering the unloading in a certain period. Under this assumption, the shipping charges incurred at the delivery destination are calculated for a certain period such as a month or a year.

FIG. 1 shows the functional configuration of the ship stoppage estimation device 100 according to the present embodiment. In the present embodiment, as an index regarding the arrears when the target article is delivered to a certain delivery destination A using a ship, the arrears time generated at the delivery destination A for a certain period of time, and the arrears fee are used. Ask.
Reference numeral 200 denotes a database, in which actual information is accumulated and stored. The actual information includes the actual information of the arrival date / time, the berthing date / time, and the departure date / time of each ship at the delivery destination A.

Reference numeral 101 denotes an input unit, which fetches actual information from the database 200. The actual information of the entire period stored in the database 200 may be imported, or the actual information of the analysis target period specified by the user may be imported.

Reference numeral 102 denotes an arrival interval distribution calculation unit which is the first distribution calculation means, and calculates the distribution of the arrival interval of the ship at the delivery destination A based on the actual information captured by the input unit 101. The distribution of the arrival intervals of ships at the delivery destination A is calculated according to a predetermined probability density function, and in this embodiment, an exponential distribution probability density function as described later.

Reference numeral 103 denotes a cargo handling time distribution calculation unit which is a second distribution calculation means, and based on the actual information captured by the input unit 101, the time required for unloading one ship at the delivery destination A (hereinafter, cargo handling time). ) Calculate the distribution. The distribution of cargo handling time per ship at the delivery destination A is calculated according to a predetermined probability density function, and in this embodiment, a probability density function of a normal distribution as described later.

Reference numeral 104 denotes a ship-by-ship stagnation time calculation unit, which is a ship-by-ship stagnation time calculation means. The ship arrival interval distribution calculated by the arrival interval distribution calculation unit 102 and the cargo handling time distribution calculation unit 103 calculated 1 By applying the queuing theory based on the distribution of cargo handling time per vessel, the arrears time per vessel at the delivery destination A is calculated.

Reference numeral 105 denotes a stagnation charge calculation unit, which is an index calculation means, and a stagnation that occurs at the delivery destination A for a certain period of time based on the stagnation time per vessel calculated by the stagnation time calculation unit 104 for each vessel. Ask for ship time and even berth charges. In this case, the detention charge calculation unit 105 treats the total amount of unloading in a certain period as a constant, as described above. In this embodiment, although details will be described later, the relationship between the amount of unloading per vessel and the arrears time per vessel, which occurs at the delivery destination A for a certain period of time, and the unloading per vessel. Find the relationship between the amount of cargo and the time spent in the ship per day. Then, the unloading charge calculation unit 105 uses the information on the arrears charge per unit time set for each ship type, and the unloading amount per ship generated at the delivery destination A for a certain period of time. And the relationship between the daily charge and the daily charge.

Reference numeral 106 denotes an output unit, which outputs the result obtained by the detention charge calculation unit 105. The output means, for example, displaying the result on the display 108 or sending the result to an external device of the apparatus 100.

107 is an input device such as a pointing device or a keyboard, and 108 is a display.

FIG. 2 is a flowchart showing a ship stagnation estimation method by the ship stagnation estimation device 100 according to the embodiment.
In step S1, the input unit 101 takes in the actual information from the database 200. In the present embodiment, for example, the past 10 years are set as the analysis target period, and the actual information including the actual information of the arrival date / time, the berthing date / time, and the departure date / time of each ship at the delivery destination A is taken in.

In step S2, the arrival interval distribution calculation unit 102 calculates the distribution of the arrival interval of the ship at the delivery destination A based on the actual information acquired in step S1.
FIG. 3 shows an example of the frequency distribution of the arrival intervals of ships. The horizontal axis of FIG. 3 represents the arrival interval (day) of the ship, and the vertical axis represents the ratio. As mentioned above, the arrival interval of vessels is greatly affected by fluctuations in departures from loading ports and differences in lead times to production bases, and has randomness. Therefore, an exponential distribution with an average value of 1 / λ was assumed. Good agreement is shown with the probability density function shown in (Equation 1). The parameter λ can be obtained by a maximum likelihood estimation method or the like.

Here, in order to apply the queuing theory, the ship arrival rate (the number of ships arriving per day) (ships / day) at the delivery destination A is calculated. Since the average value 1 / λ is the arrival interval of ships, the reciprocal λ is the ship arrival rate (ships / day). In this embodiment, the ship arrival rate λ (ship / day) was 0.32.

In step S3, the cargo handling time distribution calculation unit 103 calculates the distribution of cargo handling time per ship at the delivery destination A based on the actual information captured in step S1.
The cargo handling time per vessel is calculated as the time required from the estimated time of berth (ETB) to the estimated time of departure (ETD) of the vessel. FIG. 4 shows an example of the frequency distribution of cargo handling time per ship. The horizontal axis of FIG. 4 represents the cargo handling time (day / ship) per ship, and the vertical axis represents the ratio. Since the equipment used for unloading is performing according to its performance, the distribution of cargo handling time per ship is the probability shown by the normal distribution of mean value α and standard deviation σ (Equation 2). Shows good agreement with the density function. The mean value α and the standard deviation σ can be obtained by the maximum likelihood estimation method or the like. In the present embodiment, the mean value α is 2.37 and the standard deviation σ is 1.21.

Here, in order to apply the queuing theory, the ship processing rate (the number of ships processed per day) (ships / day) at the delivery destination A is calculated. The reciprocal of the average value α is the ship processing rate μ (ship / day). In this embodiment, the ship processing rate μ = 1 / α (ship / day) was 0.42.

In step S4, the ship-by-ship arrears time calculation unit 104 queues based on the ship arrival rate λ calculated in step S2, the mean value α, standard deviation σ, and ship processing rate μ calculated in step S3. By applying the theory, the berth time per vessel at the delivery destination A is calculated.
Arrival is exponential distribution, processing (service) is normally distributed, window is given by 1 queue, and the time spent per ship (average waiting time per ship) W _q (days / ship) is (Equation). It can be calculated from the formula of Polazek Hinchin in 3). In this embodiment, the staying time W _q (days / ship) per ship is 4.8.

In step S5, the berth charge calculation unit 105 obtains the berth time that occurs at the delivery destination A for a certain period of time based on _{the berth time W q per vessel calculated in step S4.}
Normally, in order to carry out stable operations at the delivery destination, operations are carried out so that fluctuations in unloading amount and daily usage amount can be suppressed to a small extent. Therefore, there is a strong correlation between the unloading amount and the processing rate, and when unloading in a certain period is taken into consideration, the total unloading amount can be considered to be constant. Therefore, under the assumption that the total amount of unloading is constant, if the daily prorated amount of the total amount of unloading in a certain period is set as unload (ton / day), the ship arrival rate λ (ship / day) and (Equation 4) holds using the unloading amount lot (ton / ship) per ship.
lot × λ = unloaded ・ ・ ・ (Equation 4)

Next, the relationship between the unloading amount lot (ton / ship) per ship and the ship processing rate μ (ship / day) will be examined. Since the ship processing rate μ (ship / day) is the number of ships processed per day, the reciprocal 1 / μ is the cargo handling time (day / ship) per ship.
Here, when unloading, it takes time to prepare for arrival at the port such as turn time and setup time. Since this time (called the actual unloading outside time) arrival (day / ship) is a fixed time to some extent, it can be considered as a constant. Therefore, the actual unloading time per ship is ((1 / μ) -arrange). In addition, the unloading capacity (ton / day) can be considered as a constant, assuming that the equipment is performing according to its performance. From the above, (Equation 5) is derived.
Availability = lot / ((1 / μ) -arrange) ・ ・ ・ (Equation 5)

Incorporating (Equation 4) and (Equation 5) into (Equation 3), the time spent per vessel (average waiting time per vessel) assuming that the total amount of unloading in a certain period is constant. ) W _q is given by (Equation 6). From (Equation 6), as shown in the characteristic line 501 of FIG. 5, _{the relationship between the unloading amount lot (ton / ship) per ship and the staying time W q} (day / ship) per ship. Can be calculated.

In addition, the berth time per day (average waiting time per day) W _q ´ (day / day) is the berth time W _q (day / ship) per ship and the ship arrival rate λ (ship / ship / day). It is the product of (days) and is given by (Equation 7). Therefore, as shown in the characteristic line 502 of FIG. 5, the relationship between the unloading amount lot (tons / ship) per ship and the staying time W _q ′ (days / day) per day is to be obtained. Can be done.

In this embodiment, unload = 38,000 (tons / day), availability = 57,000 (tons / day), arrival = 5 (hour / ship) = 0.21 (days / ship), which are the results of actual measurement. It was examined using it. In addition, σ / α is a volatility, but assuming that the shape of the distribution of processing does not fluctuate significantly even if the amount of unloading fluctuates, the average value α and standard deviation σ obtained from the actual results are used. There was.
As shown in the characteristic line 501 of FIG. 5, the shortest staying time per vessel is when the unloading amount is around 60,000 (tons / vessel). However, as shown in the characteristic line 502, when considering a certain period of time, the waiting time (here, the staying time per day (days / day)) is the unloading amount lot (tons) per ship. The larger the / ship), the better the result. In other words, it is shown that the time spent in a ship per day is shorter when transported by a large vessel.

In step S6, the berth charge calculation unit 105 uses the information on the arrears charge per unit time to obtain the arrears charge generated at the delivery destination A for a certain period of time.
Ships are classified into ship types such as HANDY, PMAX, CAPE, and VL according to their loadable capacity. For each ship, the stagnation fee incurred when the ship is stagnation for a unit time is fixed, but this stagnation fee is about the same amount for each ship type. Here, according to Table 1, the ship types 1 to 4 are classified according to the loadable capacity from the past actual ship detention charges, and the average thereof is obtained and used as the ship type detention charges.

In order to avoid unnecessary transportation, the ship transports an almost full amount commensurate with the loadable capacity. Therefore, the examination was conducted on the assumption that the unloading amount and the loading amount per ship are the same. As shown in FIG. 6, by applying the arrears fee for each vessel type in Table 1 to the relationship between the unloading amount per vessel and the arrears time per day obtained in FIG. 5, 1 The relationship between the amount of unloading lot (ton / ship) per ship and the daily charge (yen / day) can be derived. In this example, when a ship type 2 (loadable capacity: 55 or more and less than 120 (thousand tons)) is used and the cargo is transported with the loadable capacity almost full, the ship is delinquent that occurs at the delivery destination A for a certain period of time. It turns out that the charge can be suppressed.

In step S7, the output unit 106 outputs the results obtained in steps S5 and S6.

As described above, by grasping the tendency of the arrival interval of ships at the delivery destination A and the cargo handling time per ship, the correlation between the arrival rate and the processing rate is taken into consideration when applying the queuing theory. , It is possible to obtain the queuing time that occurs at the delivery destination A for a certain period of time, and the queuing fee. This makes it possible to consider appropriate measures to reduce berth charges.

The present invention is not limited to iron ore and coal in a steel maker, but when a target article such as a raw material, a material, a product, or a product is delivered to a delivery destination such as a factory, a commercial facility, or an inventory base by using a ship. , It is applied to estimate the arrears time and arrears caused by making a ship wait. For example, crude oil from chemical manufacturers and oil manufacturers, and LNG and coal from electric power manufacturers are also transported from overseas to domestic delivery destinations by ship. A general contract stipulates a standard cargo handling time when the transported target goods are loaded and unloaded at a domestic delivery destination, and if this standard time is exceeded, a penalty will be delinquent. The arrears fee will be paid in proportion to the amount of ships and transportation. Therefore, the present invention in which the arrears time and the arrears fee generated at the delivery destination are obtained is widely applicable.

Although the present invention has been described above with the embodiments, the above-described embodiments are merely examples of embodiment of the present invention, and the technical scope of the present invention is interpreted in a limited manner by these. It must not be. That is, the present invention can be implemented in various forms without departing from the technical idea or its main features.
A ship stagnation estimation device to which the present invention is applied is realized by, for example, a computer device including a CPU, ROM, RAM, and the like. Although the ship retention estimation device 100 is shown as one device in FIG. 1, it may be configured by, for example, a plurality of devices.
The present invention also provides software (programs) that realize the functions of the present invention to a system or device via a network or various storage media, and the computer of the system or device reads and executes the program. It is feasible.

100: Ship lag estimation device 101: Input unit 102: Arrival interval distribution calculation unit 103: Cargo handling time distribution calculation unit 104: Ship berth time calculation unit 105: Ship lag calculation unit 106: Output unit 107: Input device 108 : Display 200: Database

Claims (10)

It is a ship stagnation estimation device that obtains an index related to stagnation when delivering the target goods to the delivery destination using a ship.
An input means for importing actual information including the arrival date and time, berthing date and time, and departure date and time of each ship at the delivery destination from the database.
Based on the arrival date and time of the record information, which is number of vessels of vessel vessels distribution arrival interval in the delivery destination calculated according to a predetermined first probability density function, to arrive in per unit time in the delivery destination vessels The first distribution calculation means for calculating the arrival rate λ and
Based on the berthing date and time and the berthing date and time of the actual information, the distribution of cargo handling time, which is the time required for unloading per ship at the delivery destination, is calculated according to a predetermined second probability density function , and per ship. The average value α of the cargo handling time, the standard deviation σ of the cargo handling time per ship, and the second distribution calculation means for calculating the ship processing rate (= 1 / α) μ at the delivery destination.
The ship arrival rate λ, which is a parameter representing the distribution of the arrival intervals of ships calculated by the first distribution calculation means, and the parameter representing the distribution of cargo handling time per ship calculated by the second distribution calculation means. By substituting the mean value α, the standard deviation σ, and the ship processing rate μ into the equation of the queue theory , the ship stagnation time W per ship at the delivery destination is calculated for each ship. Ship time calculation means and
An index calculation means for calculating the stagnation time generated at the delivery destination for a certain period of time based on the stagnation time W per ship calculated by the stagnation time calculation means for each ship .
It is provided with an output means for outputting the berthing time generated at the delivery destination obtained by the index calculation means.
The index calculation means is a ship detention estimation device characterized in that the total amount of unloading in a certain period is treated as constant. The formula of the queuing theory is
W = {λ / (μ ・ (μ−λ))} ・ {(1+ (σ / α)) ² ) / 2}
The ship stagnation estimation device according to claim 1, wherein the ship is said to be. The index calculation means covers the fixed period, the relationship between the unloading amount per ship and the staying time per ship, and the unloading amount per ship and the staying time per day. The ship stagnation estimation device according to claim 1 or 2, wherein the relationship with the ship is obtained. The index calculation means is characterized in that it obtains the relationship between the amount of unloading per ship and the daily charge for a certain period of time by using the information on the charge for the charge per unit time. The ship stagnation estimation device according to claim 3. The ship stagnation estimation device according to claim 4 , wherein the information on the stagnation fee per unit time is set for each ship type. In the index calculation means, the total amount of unloading is calculated from the distribution of the arrival intervals of the ships calculated by the first distribution calculation means, and the number of ships arriving per day at the delivery destination and one ship. The arrears estimation device according to any one of claims 1 to 5 , wherein the amount of unloading per ship is used. The index calculation means is the cargo handling time per ship, which is obtained by subtracting the actual unloading time including at least one of the port entry preparation time and the setup time from the time required from the berthing to the berthing of the ship. The ship stagnation estimation device according to any one of claims 1 to 6 , wherein the ship stagnation estimation device is characterized. The arrears estimation device according to claim 7 , wherein the actual unloading outside time is a constant. It is a method of estimating ship stagnation that obtains an index related to stagnation when delivering the target goods to the delivery destination using a ship.
The input means is an input procedure for fetching the actual information including the arrival date / time, berthing date / time, and departure date / time of each ship at the delivery destination from the database.
The first distribution calculation means calculates the distribution of the arrival interval of the ship at the delivery destination according to a predetermined first probability density function based on the arrival date and time of the actual information , and per unit date and time at the delivery destination. The first distribution calculation procedure for calculating the ship arrival rate λ, which is the number of arriving ships,
The cargo handling time, which is the time required for the second distribution calculation means to unload one vessel at the delivery destination according to a predetermined second probability density function based on the berthing date and time and the berthing date and time of the actual information. Second distribution calculation that calculates the distribution and calculates the average value α of the cargo handling time per ship α, the standard deviation σ of the cargo handling time per ship, and the ship processing rate (= 1 / α) μ at the delivery destination. Procedure and
The ship arrival time calculation means for each ship has the ship arrival rate λ, which is a parameter representing the distribution of the arrival intervals of the ships calculated in the first distribution calculation procedure, and one ship calculated in the second distribution calculation procedure. By substituting the average value α, the standard deviation σ, and the ship processing rate μ, which are parameters representing the distribution of cargo handling time per ship, into the equation of the queue theory, the stagnation per ship at the delivery destination The procedure for calculating the arrears time for each ship to calculate the ship time W,
An index calculation procedure for calculating the stagnation time generated at the delivery destination for a certain period of time based on the stagnation time W per ship calculated by the index calculation means for each ship stagnation time calculation procedure, and an index calculation procedure.
The output means has an output procedure for outputting the berthing time generated at the delivery destination obtained by the index calculation procedure .
The index calculation procedure is a method for estimating a ship stagnation, which comprises treating the total amount of unloading in a certain period as a constant. It is a program to obtain an index related to arrears when delivering the target goods to the delivery destination using a ship.
An input means for importing actual information including the arrival date and time, berthing date and time, and departure date and time of each ship at the delivery destination from the database.
Based on the arrival date and time of the record information, which is number of vessels of vessel vessels distribution arrival interval in the delivery destination calculated according to a predetermined first probability density function, to arrive in per unit time in the delivery destination vessels The first distribution calculation means for calculating the arrival rate λ and
Based on the berthing date and time and the berthing date and time of the actual information, the distribution of cargo handling time, which is the time required for unloading per ship at the delivery destination, is calculated according to a predetermined second probability density function , and per ship. The average value α of the cargo handling time, the standard deviation σ of the cargo handling time per ship, and the second distribution calculation means for calculating the ship processing rate (= 1 / α) μ at the delivery destination.
The ship arrival rate λ, which is a parameter representing the distribution of the arrival intervals of ships calculated by the first distribution calculation means, and the parameter representing the distribution of cargo handling time per ship calculated by the second distribution calculation means. By substituting the mean value α, the standard deviation σ, and the ship processing rate μ into the equation of the queue theory , the ship stagnation time W per ship at the delivery destination is calculated for each ship. Ship time calculation means and
An index calculation means for calculating the stagnation time generated at the delivery destination for a certain period of time based on the stagnation time W per ship calculated by the stagnation time calculation means for each ship .
The computer is made to function as an output means for outputting the arrears time generated at the delivery destination obtained by the index calculation means.
The index calculation means is a program characterized in that the total amount of unloading in the fixed period is treated as constant.

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