JP7643637B2 - Material supply support device, method and program - Google Patents

Description

One aspect of the present invention relates to a material supply support device, method, and program used to support the task of supplying materials to multiple locations, for example, when a disaster occurs.

The task of delivering and supplying resources, goods, and other materials to multiple locations using vehicles is an essential task in modern society. In particular, in the event of a large-scale disaster, the task of transporting and supplying power equipment, water, food, and other necessary materials to points of demand using vehicles is extremely important in preventing the depletion of materials at each location.

However, when the number of supply points is significantly greater than the number of vehicles, it is inevitable that some points will run out of supplies because the supplies cannot be delivered in time. Therefore, for example, Non-Patent Document 1 proposes a technology to supply supplies by excluding points where supplies will inevitably run out from the supply route, and determining the route that minimizes the maximum time it takes for supplies to run out at each point as the optimal supply route.

M. Ogawa and 3 others, “A route searching method using two-dimensional coordinates”, IEICE, DOI:10.34385/proc.63.E4-3, 2020.

However, the technology described in Non-Patent Document 1 determines the optimal supply route after excluding in advance points where resource depletion is unavoidable. As a result, there is a tendency for a large number of points to be excluded from the supply route of resources.

This invention has been made in light of the above circumstances, and aims to provide technology that makes it possible to determine the supply route of materials to a location while reducing the number of locations excluded from the supply route as much as possible.

In order to solve the above problem, one aspect of the material supply support device or method according to the present invention is to, when performing a process to support the supply of materials to a first set of points using a transport medium, acquire parameter information related to the supply of the materials to the first set of points and between each of the points, and based on the acquired parameter information, determine the number of points to be abandoned for abandoning the supply of the materials so that the time to run out of the materials in the first set of points is minimized and the number of points to be supplied with the materials is maximized. Then, for a second set of points obtained by excluding the number of points from the first set of points equivalent to the number of points to be abandoned, a material supply route that minimizes the time to run out of the materials is determined, and support information including information representing the material supply route is generated and output.

According to one aspect of the invention, when determining the optimal route for supplying materials, the number of points to be abandoned is first determined so as to minimize the number of points to be abandoned, and the optimal supply route for materials is determined with a number of points equivalent to the determined number of points as points to be abandoned. Therefore, it is possible to determine an optimal supply route that does not cause a shortage of materials while minimizing the number of points to be abandoned.

In other words, according to one aspect of the present invention, it is possible to provide technology that makes it possible to determine a supply route for materials to demand points while reducing, as much as possible, the number of demand points that are excluded from the supply route for materials.

FIG. 1 is a block diagram showing an example of a hardware configuration of a materials supply support device according to an embodiment of the present invention. FIG. 2 is a block diagram showing an example of the software configuration of the material supply support device according to an embodiment of the present invention. FIG. 3 is a flow chart showing an example of the overall processing procedure and processing contents of the material supply support control executed by the control unit of the material supply support apparatus shown in FIG. FIG. 4 is a flowchart showing an example of the procedure and contents of the triage point number determination process of the processing procedure shown in FIG. FIG. 5 is a flowchart showing an example of the procedure and contents of the optimum route determination process of the procedure shown in FIG. FIG. 6 is a diagram illustrating an example of travel time between points. FIG. 7 is a diagram illustrating an example of a process for determining triage candidates. FIG. 8 is a diagram for explaining an example of determining an optimal route.

Below, an embodiment of the present invention is described with reference to the drawings.

[One embodiment]
(Configuration example)
The materials supply support device SV according to the embodiment of the present invention is, for example, a server computer and is located on the web or in the cloud. Note that the materials supply support device SV may also be a personal computer used exclusively by a local government or a delivery company.

Figures 2 and 3 are block diagrams showing examples of the hardware and software configurations of the material supply support device SV, respectively.

The material supply support device SV has a control unit 1 that uses a hardware processor such as a central processing unit (CPU). A storage unit having a program storage unit 2 and a data storage unit 3, and a communication interface unit (hereinafter referred to as the communication I/F unit) 4 are connected to this control unit 1 via a bus 5.

Under the control of the control unit 1, the communication I/F unit 4 uses a communication protocol defined by a network (not shown), including the Internet, to send and receive information data, for example, between a management terminal used by a local government or delivery company, or between a vehicle terminal installed in a vehicle serving as a transport medium.

The program memory unit 2 is configured, for example, by combining a non-volatile memory such as a HDD (Hard Disk Drive) or SSD (Solid State Drive) as a storage medium that can be written to and read from at any time, and a non-volatile memory such as a ROM (Read Only Memory), and stores application programs necessary for executing various control processes according to one embodiment of the present invention, in addition to middleware such as an OS (Operating System).

The data storage unit 3 is, for example, a combination of a non-volatile memory such as an HDD or SSD as a storage medium that can be written to and read from at any time, and a volatile memory such as a RAM (Random Access Memory), and includes a parameter information storage unit 31 and an optimal route information storage unit 32 as storage areas in one embodiment.

The parameter information storage unit 31 is used to store parameter information input from the management terminal of the local government or delivery company. The parameter information includes multiple locations to which supplies are to be supplied and attribute information related to the supply of the supplies between those locations. The attribute information includes, for example, location information for each location, the expected travel time between each location, and the expected stay time at each location.

The optimal route information memory unit 32 is used to store optimal route information representing the optimal delivery route determined by the control unit 1.

The control unit 1 includes, as processing functions according to one embodiment of the present invention, a parameter information acquisition processing unit 11, a triage point number determination processing unit 12, an optimal route determination processing unit 13, and a support information output processing unit 14. All of these processing units 11 to 14 are realized by causing the hardware processor of the control unit 1 to execute application programs stored in the program storage unit 2.

In addition, some or all of the above processing units 11 to 14 may be realized using hardware such as an LSI (Large Scale Integration) or an ASIC (Application Specific Integrated Circuit).

Prior to the delivery of goods, the parameter information acquisition processing unit 11 receives parameter information sent via a network, for example from a management terminal of a local government or a delivery company, via the communication I/F unit 4, and performs processing to store the received parameter information in the parameter information storage unit 31.

The triage point number determination processing unit 12 performs a process of determining the number of points at which the supply of materials must be abandoned (triage) based on the parameter information stored in the parameter information storage unit 31. An example of this process of determining the number of triage points will be described in detail in the operation example.

The optimal route determination processing unit 13 determines which specific points are to be abandoned according to the determined number of triage points. Then, for the set of supply target points excluding the points to be abandoned, the optimal delivery route that minimizes the time required for depletion of materials is determined, and information representing the determined optimal route is stored in the optimal route information storage unit 32. An example of this optimal route determination process will also be described in detail in the operation example.

The support information output processing unit 14 generates information to support the supply of goods, including the optimal route information stored in the optimal route information storage unit 32, and transmits the generated support information from the communication I/F unit 4 to, for example, a management terminal of a local government or delivery company, or a terminal installed in a delivery vehicle.

(Example of operation)
Next, an example of the operation of the material supply support device SV configured as above will be described.
FIG. 3 is a flow chart showing an example of a materials supply support operation executed by the control unit 1 of the materials supply support device SV.

(1) Acquisition of Parameter Information When a disaster occurs, for example, a local government or a delivery company identifies all points where supplies need to be supplied, and inputs parameter information including the location information of each point, the estimated travel time between each point, the estimated stay time at each point, etc., into a management terminal. The parameter information is then transmitted from the management terminal to the supplies supply support device SV via a network (not shown).

In response to this, in step S10, the control unit 1 of the material supply support device SV, under the control of the parameter information acquisition processing unit 11, receives the parameter information transmitted from the management terminal via the communication I/F unit 4, and stores the received parameter information in the parameter information storage unit 31.

For example, suppose there are n+1 points on a two-dimensional plane indicating the disaster area, and these points are denoted as v _i , i ∈ {0, 1, ..., n}, n ∈ Z. In this case, position information on the two-dimensional plane of each point v _i (e.g., latitude and longitude information), the estimated travel time t(v _i , v _j ) ∈ R _{> 0} between each point v _i , the remaining time d _i ∈ R _{> 0} at time t = 0, and the estimated stay time p _i ∈ R _{> 0} at each point are input at the management terminal, and this information is sent to the supplies supply support device SV and stored in the parameter information storage unit 31.

(2) Determining the Number of Triage Points When the above parameter information is acquired, in step S20, the control unit 1 of the materials supply support device SV first executes a process of determining the number of triage points under the control of the triage point number determination processing unit 12 as follows.

Figure 4 is a flowchart showing an example of the processing procedure and processing content of the triage point number determination process performed by the triage point number determination processing unit 12.

(2-1) Selection of the route with the shortest maximum depletion time First, in step S21, the triage point number determination processing unit 12 defines all routes that can be set for all supply points as the first set of points, and calculates the maximum depletion time of materials for each of the defined routes.

により算出する。 For example, when a vehicle travels between points along route r, the time to run out of a commodity T _i (r) can be calculated from the arrival time a _i (r) at each point v _i as follows:

It is calculated as follows.

が経路ｒの与える最大枯渇時間であることから、全経路について最大枯渇時間を求めたとき、その最小値

を与える経路が、最も枯渇時間の少ない最適経路であり、最小値が最適値であると、ステップＳ２２により定義する。 Then, the triage point number determination processing unit 12 calculates the maximum value of each T _i

Since is the maximum exhaustion time given by route r, when the maximum exhaustion time is calculated for all routes, the minimum value

In step S22, the route that gives the minimum exhaustion time is defined as the optimal route, and the minimum value is defined as the optimal value.

In this case, if the maximum depletion time T* of the defined optimal route is negative, it is possible to supply materials to all points before they run out. On the other hand, if the maximum depletion time T* is positive, it is necessary to set points where the supply of materials will be abandoned.

(2-2) Defining the range of the optimal exhaustion time Therefore, in step S23, the triage point number determination processing unit 12 first defines multiple candidates for the number of points to be abandoned, and roughly calculates the range of values for the optimal exhaustion time for each of these numbers of points.

を定義する。 That is, the triage point number determination processing unit 12 sets the optimal value when k (<n) points are to be abandoned as T*k, and sets the range as

Define.

(2-3) Calculation of Optimum Range of Number of Points to be Abandoned Next, in steps S24 and S25, the triage point number determination processing unit 12 calculates an upper limit value MAX _k and a lower limit value MIN _k that satisfy the optimum range of the number of points to be abandoned, respectively.

Basically, the values of the upper limit value MAX _k and the lower limit value MIN _k decrease as the value of k increases. Therefore, the triage point number determination processing unit 12 determines the number of points to be abandoned in descending order of the probability that the closed interval [MIN _k , MAX _k ] representing the above range includes the vicinity of 0 when k is increased from 1.

と定義する。 (2-3-1) Calculation of the upper limit value MAX _k Let S _k be a set of points obtained by appropriately discarding k points from n points. Let R _k be a set of routes that visit all points included in the set S _k. Appropriately select an element r _k of the set R _k ,

It is defined as:

を満たす値MIN_k を算出する。 (2-3-2) Calculation of Lower Bound MIN _k A relaxation problem is applied to calculate the lower bound MIN _k .
The triage point number determination processing unit 12 defines a set of (n-k) points obtained by discarding any k points from the n points as S^ _k :={(n-k) point set}, and defines a set of all routes that visit all the point set S _k ∈ S^ _k included in S^ _k as R^ _k :={ _Rk }. Then, the triage point number determination processing unit 12:

Calculate the value MIN _k that satisfies the following:

の下限値が求められことを利用する。 Specifically, all elements of a certain S _k are aggregated to one appropriate point, and this point is visited in the optimal order,

We use the fact that the lower limit of

First, a method for calculating the exhaustion time at a location will be described.
Arbitrarily set a point where the points are aggregated. At this time, d _i and p _i of each point do not change. We will explain the visiting order on the points and the calculation method of the maximum depletion time. Let the points aggregated into one point be v' ₁ , ..., v' _h , (h = n - k), and let f be the function that converts the indexes of these points into point indexes on the original two-dimensional plane.

と表される。 For example, if point _v'1 was point _v'j in the original two-dimensional plane, then f(1) = j, the remaining time and the required stay time are d' _i and _p'i (i ≤ h), respectively, and the remaining time d' _i is

This is expressed as:

In addition, when moving between points _v'i , no travel time is incurred because the points are the same coordinates, but there is a time (idle time) during which the vehicle is unable to supply goods between the time it finishes supplying goods to one point and the time it starts supplying goods to the next point. This idle time reflects the travel time on a two-dimensional plane. Therefore, the length of the idle time depends on the operation of the vehicle moving from the point where it has finished supplying goods to the next supply point.

と定義される。 Now, when a vehicle is about to supply goods to a point v' _j , if the idle time is t _j , this idle time t _j is

It is defined as follows.

The route that minimizes the maximum exhaustion time at a point is the route visited in the order of smallest _p'i + d' _i, which is the sum of the residence time and the exhaustion time. This can be easily shown because the optimal decision in the scheduling problem of minimizing the delivery tardiness is equivalent to processing jobs in the order of shortest delivery time.

と表される。ここで、Ｌ_b はｐ′_i ＋ｄ′_i が小さい順に訪れる経路で最後に訪れる地点の枯渇時間Last(Ｒ_k)よりも大きい。 Now, let L _b (R _k ) be the maximum starvation time of the routes visited in ascending order of p' _i + d' _i . Then, the maximum starvation time L _b (R _k ) is

Here, L _b is greater than the exhaustion time Last(R _k ) of the last point visited on the path visited in ascending order of p′ _i +d′ _i .

が任意のＲ_k ∈Ｒ^_k に対して成立する。これより、

の下限値を求め、その値をMIN_k とすれば十分である。 Therefore,

holds for any R _k ∈ R̂ _k . From this,

It is sufficient to determine the lower limit of and set this value as MIN _k .

と表現できる。 The exhaustion time Last(R _k ) of the last visited point is

This can be expressed as follows.

は、

の最小値から、

の最大値を引いたものとして求められる。 Therefore, the minimum exhaustion time of the last visited point is

teeth,

From the minimum value of

It is calculated by subtracting the maximum value of

の最小値、つまり地点の滞在時間＋アイドルタイムの最小値から順にｎ－ｋ番目に小さい値までの和

の最大値、つまりｐ_l ＋ｄ_l （ｌ＝１，２，…，ｎ）の最大値より、下限値MIN_kを求めることができる。 That is,

The minimum value of

The lower limit value MIN _k can be obtained from the maximum value of p _l +d _l (l=1, 2, . . . , n).

(2-4) Estimation of the Number of Triage Points In steps S26 to S28, the triage point number determination processing unit 12 next estimates the number of triage points k as follows, based on the upper limit value MAX _k and the lower limit value MIN _k that indicate the optimal range of the number of points to be abandoned.

となる。 That is, if the probability of the existence of the optimum value in the range of x ∈ [MIN _k , MAX _k ] follows the probability distribution function f(x), the probability P _k that the optimum value exists in the vicinity of 0 (below |ε|) is given by:

It becomes.

Here, ε and the function f(x) are appropriately set to find the probability _Pk . However, if the optimum value does not exist near 0 as is, there are two possible cases: the maximum depletion time is too large or too small. If k is larger than 0, it is necessary to exclude it from the candidates for the number of points to be reliably abandoned.

のように定義する。そして、上記SCORE_k が大きい地点数ｋの順に、放棄する地点数の第一候補、第二候補、…を設定する。 Therefore, the suitability value SCORE _k is used as a candidate for the number of locations to be abandoned.

Then, the first candidate, second candidate, ... for the number of locations to be abandoned are set in the order of the number of locations k with the largest SCORE _k .

(3) Determination of Optimal Route Next, in step S30, the control unit 1 of the material supply support device SV calculates an optimal route for material supply under the control of the optimal route determination processing unit 13. Note that the following description will be given taking as an example a case where the branch and bound method is used as the determination method.

Figure 5 is a flowchart showing an example of the processing procedure and processing content of the optimal route determination processing performed by the optimal route determination processing unit 13.

(3-1) Determination of Points to be Abandoned When using the branch and bound method, the optimal route determination processing unit 13 first defines a set σ consisting of all feasible solutions in step S31, and divides this set σ into an appropriate subset,
σ _i ⊂σ, ∪ _i σ _i =σ, σ _i ∩σ _j =φ(i≠j)
Divide by.

(3-1-1) Determination of a set of points to be abandoned In this example, since the solution to the optimization problem is a set of points, the optimal route determination processing unit 13 defines a subset _σi of the set of points as a set of points for which point v _i out of k points is abandoned. Then, in steps S32 and S33, the optimal route determination processing unit 13 calculates the upper and lower limits of the smallest maximum exhaustion times of routes that visit all of the set of points _σi , as follows:

That is, the optimum route determination processing unit 13 first determines the T max (r) of the route that visits the points other than the k points including the specified point among the points that have not yet been visited, in _order of the remaining time d _i , and sets this as the upper limit value.

Next, for the lower limit value, the optimum route determination processing unit 13 aggregates all unvisited points other than the k points including the specified point into one arbitrary point, finds T _max (r) of the route visited in ascending order of the sum of the residence time and exhaustion time at the point, and determines this as the lower limit value.

Next, in step S34, the optimal route determination processor 13 selects two different solution sets σ _i and σ _j , and compares the upper limit value of one solution set σ _i with the lower limit value of the other solution set σ _j for these solution sets σ _{i and σ j .} Then, in step S35, it is determined whether the lower limit value of the solution set σ _j is greater than the upper limit value of the solution set σ _i .

If the result of the comparison is that the lower limit value of the set σ _j is greater than the upper limit value of the set σ _i , the optimal route determination processing unit 13 determines that the feasible solutions included in the set σ _j cannot be optimal solutions, and abandons the search for this set in step S37. On the other hand, if the upper limit value of the set σ _i is greater than the lower limit value of the set σ _j , the optimal route determination processing unit 13 stores the points specified by the above sets as candidates for supply targets of materials in step S36.

Then, the optimum route determination processing unit 13 determines in step S38 whether the number of points specified by each set σ _i has reached k, and repeats the processing in steps S31 to S38 until the number of points specified reaches k.

(3-2) Determination of Optimal Route When the number of specified points reaches k, the optimal route determination processing unit 13 proceeds to step S39 and performs processing for determining the optimal route.

That is, the optimal route determination processing unit 13 calculates the optimal route and maximum exhaustion time for each of the sets of points that have not been abandoned. Then, the optimal route is determined to be the route with the smallest maximum exhaustion time, and information representing this optimal route is stored in the optimal route information storage unit 32.

(4) Output of Support Information Finally, in step S40, the control unit 1 of the material supply support device SV, under the control of the support information output processing unit 14, reads out information representing the optimum route from the optimum route information storage unit 32, and generates support information including the information representing the read optimum route. In addition to the optimum route information, the support information includes, for example, information specifying the type and amount of materials, road congestion information, weather information, etc. The road congestion information and weather information, etc. can be obtained, for example, from a website on the Web.

(Specific example of operation)
Next, a specific example of the processing operation described above will be explained.
Let us assume that the points in the disaster area are _v0 , _v1 , _v2 , _v3 , _v4 , _v5 , and _v6 . Let us also assume that the remaining time until supplies run out at the supply target points _v1 , _v2 , _v3 , _v4 , _v5 , and _v6 are _d1 = 7, _d2 = 9, _d3 = 8, _d4 = 8, _d5 = 8, and _d6 = 9, respectively, and the residence time for supplying supplies at each point is _p1 = 5, _p2 = 3, p3 = 4, _p4 = ₄ , _p5 = 4, and _p6 = 3, respectively.
FIG. 6 is a diagram showing an example of travel time between each point in this case, the unit of which is time [h].

First, determine the number of potential triage points.
7 is a diagram showing an example of a process for determining triage candidates. Let us assume that the probability distribution function f(x) is a normal distribution with a mean (MAXi + MINi)/2 and a standard deviation (|MAXi + MINi|)/4, and that the vicinity of 0 is |ε|=0.5 or less.

In this state, when the range of the minimum value of the maximum depletion time is calculated when the number of points to be abandoned is set to 1, 2, 3, 4, or 5, the upper and lower limits are the values shown in Fig. 7. When the above conditions are applied to these calculated values, the probability _Pk when the number of points to be abandoned is 1 or 2 is both 0.

Based on the above results, in this example, the first candidate for the number of abandoned points is determined to be three, and the second candidate is determined to be four.

Next, the optimum route is determined by reflecting the number of triage points.
For example, if the number of triage points is set to three, which is the first candidate, then among all routes that supply supplies to the three target points, the route with the shortest maximum depletion time is:
v ₀ → v ₄ → v ₂ → v ₆
The maximum depletion time on this route is 0 or less. Therefore, in this case, there is no need to calculate the second candidate number of triage points, which is four, and the process of determining the optimal route ends here. FIG. 8 shows an example of the determined optimal route shown on a two-dimensional plane.

(Action and Effects)
As described above, in one embodiment, for multiple points to be supplied with materials, a route that minimizes the maximum depletion time of the materials is identified from multiple material supply routes that can be set for each point based on parameter information including previously given location information, stay time at each point, and travel time between points, and if there is a point on this route where the supply of materials is to be abandoned, an optimal range for the number of points is obtained and candidates for the number of points to be abandoned are determined within this range. Next, which points are to be abandoned among the determined candidates for the number of points to be abandoned, and an optimal delivery route that minimizes the depletion time of the materials is determined for the set of supply points other than those to be abandoned, and the determined optimal route is output.

Therefore, when determining the optimal route for supplying materials, the number of points to be abandoned is first calculated so as to minimize the number of points to be abandoned, and the optimal supply route for materials is determined with points equivalent to this number as the points to be abandoned. This makes it possible to determine an optimal supply route that does not result in shortages of materials while minimizing the number of points to be abandoned.

In addition, when determining the number of points to be abandoned, the range of maximum depletion time is calculated for each number of points that are candidates for abandonment, and candidates for the number of points to be abandoned are selected in order of the probability that this range contains 0. As a result, it is possible to determine the optimal route that has the fewest number of points to be abandoned and the shortest maximum depletion time from among multiple candidates for the number of points to be abandoned.

[Other embodiments]
In the above embodiment, a case has been described in which the entire series of processes from the parameter acquisition process to the support information output process is executed on one server device, but all or part of the series of processes from the parameter acquisition process to the support information output process may be distributed and processed by a plurality of server devices or information processing terminals such as personal computers.

In the above embodiment, the supply of goods to multiple locations when a disaster occurs has been described as an example. However, the present invention is not limited to this, and can also be applied as a support system for delivering goods to multiple stores during normal times, for example.

In addition, as a means of transport, in addition to road vehicles such as trucks, it is possible to selectively use trains, ships, and flying objects such as drones. In addition, the functions of the material supply support device, the processing procedures and processing contents, the types of materials, the contents of the support information, etc. can be modified in various ways without departing from the spirit of this invention.

Although the embodiment of the present invention has been described in detail above, the above description is merely an example of the present invention in every respect. It goes without saying that various improvements and modifications can be made without departing from the scope of the present invention. In other words, in implementing the present invention, specific configurations according to the embodiment may be appropriately adopted.

In short, this invention is not limited to the above-described embodiment as it is, and in the implementation stage, the components can be modified and embodied without departing from the gist of the invention. Furthermore, various inventions can be formed by appropriate combinations of multiple components disclosed in the above-described embodiment. For example, some components may be deleted from all of the components shown in the embodiment. Furthermore, components from different embodiments may be appropriately combined.

SV...material supply support device 1...control unit 2...program storage unit 3...data storage unit 4...communication I/F unit 5...bus 11...parameter information acquisition processing unit 12...triage point number determination processing unit 13...optimum route determination processing unit 14...support information output processing unit 31...parameter information storage unit 32...optimum route information storage unit

Claims (6)

A supplies supply support device that supports a task of supplying supplies to a first set of points using a transportation medium,
a first processing unit for acquiring parameter information related to the supply of the material between the first set of locations and each of the first set of locations;
a second processing unit that determines a number of points to be abandoned for the supply of the material based on the parameter information so that a depletion time of the material in the first set of points is minimized and a number of points to be supplied with the material is maximized;
a third processing unit that determines a material supply route that minimizes a depletion time of the material for a second set of points obtained by excluding a number of points corresponding to the number of points to be abandoned from the first set of points;
a fourth processing unit that generates and outputs support information including information representing the material supply route. The second processing unit includes:
A process of identifying a route that minimizes a maximum depletion time of the material from among a plurality of material supply routes that can be set to the first set of points;
a process of setting a plurality of candidates for the number of points to be abandoned for the first set of points when there is a point on the identified route where the supply of the material needs to be abandoned, and calculating a range of the depletion time for each of the plurality of candidates;
The material supply support device of claim 1 performs a process of selecting from the plurality of candidates a candidate whose probability of the depletion time taking the minimum value within the range satisfies a predetermined condition, and determining the selected candidate as the number of points to be abandoned. The material supply support device of claim 2, wherein the second processing unit determines, when the minimum value of the depletion time within the range is defined by a probability distribution function, the candidates whose minimum value of the depletion time is near 0 as the number of locations to be abandoned. The third processing unit includes:
a process of determining, from the first set of points, a set of points that includes a number of points equivalent to the number of the abandonment target points and that has a minimum depletion time of the material as a set of points to be abandoned;
2. The material supply support device according to claim 1, further comprising a process of determining, as the material supply route, a route that minimizes a time required for depleting the material for the second set of points excluding the determined set of points to be abandoned. A materials supply support method, comprising: an information processing device executing a process for supporting a task of supplying materials to a first set of points using a transportation medium, the process comprising:
obtaining parameter information relating to the supply of said commodity at and between said first set of locations;
determining a number of points to be abandoned for the supply of the material based on the parameter information so that the depletion time of the material in the first set of points is minimized and the number of points to be supplied with the material is maximized;
a third processing unit that determines a material supply route that minimizes a depletion time of the material for a second set of points obtained by excluding a number of points corresponding to the number of points to be abandoned from the first set of points;
generating and outputting support information including information representing the material supply route. A program that causes a processor provided in a material supply support device to execute at least one of the processes executed by the first to fourth processing units provided in the material supply support device described in any one of claims 1 to 4.

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