Transportation planning device, transportation planning method, and transportation planning program

Abstract

Balancing the reduction in the number of drivers required with improving the working conditions for drivers is essential for developing a transportation plan that is favorable for both the transporter and the transportation characteristics. [Solution] The system comprises: a transportation planning unit that formulates a transportation plan based on the transportation conditions of the transportation plan to be formulated, past transportation conditions, and the weights of key performance indicators for transportation performance; an indicator estimation unit that estimates the weights of key performance indicators for past transportation conditions by comparing the values ​​of key performance indicators calculated based on the transportation plan formulated by the transportation planning unit with the values ​​of key performance indicators for past transportation performance calculated from past transportation performance; and an indicator setting unit that identifies past transportation conditions from among multiple past transportation conditions that have the highest similarity to the transportation conditions of the transportation plan to be formulated, and sets the weights of key performance indicators for transportation performance corresponding to the identified past transportation conditions.

Description

Technical Field

[0001] The present invention relates to a transportation planning device, a transportation planning method, and a transportation planning program, and is suitable for application to, for example, a transportation planning device related to a technique for formulating a transportation plan.

Background Art

[0002] In the logistics industry, in order to solve the shortage of the number of drivers due to the so-called 2024 problem, etc., it is required to improve transportation efficiency to reduce the number of required drivers, and to improve the workability (QoW: Quality of Work) of each driver, thereby securing driver workers. There is a trade-off between reducing the number of required drivers and improving the QoW of drivers. For this reason, the preferable balance between the two differs depending on the transportation carrier and the characteristics of the transportation to be targeted (hereinafter referred to as "transportation characteristics"). In Patent Document 1, a technique is disclosed in which a planned arrangement restriction model machine-learned using learning data as teacher data is used, and a planned arrangement for maximizing a predetermined objective function is determined based on a plan that requires correction and arbitrary KPI (Key Performance Indicators) priority information.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, reducing the number of required drivers and improving the workability of drivers are in a trade-off relationship. With the technique described in Patent Document 1, it has been difficult to formulate a good transportation plan for the transportation carrier and transportation characteristics while considering the balance between the two.

[0005] This invention has been made in consideration of the above points, and aims to propose a transportation planning device and method that can formulate a transportation plan that is favorable to transportation companies and transportation characteristics by balancing the reduction of the number of drivers required and the improvement of the ease of work for drivers. [Means for solving the problem]

[0006] To solve these problems, the present invention includes: a transportation planning unit that formulates a transportation plan based on the transportation conditions of the transportation plan to be formulated, past transportation conditions, and the weights of key performance indicators of transportation performance; an indicator estimation unit that estimates the weights of key performance indicators for past transportation conditions by comparing the values ​​of key performance indicators calculated based on the transportation plan formulated by the transportation planning unit with the values ​​of key performance indicators of past transportation performance calculated from past transportation performance; and an indicator setting unit that identifies past transportation conditions from among a plurality of past transportation conditions that have the highest similarity to the transportation conditions of the transportation plan to be formulated, and sets the weights of key performance indicators of transportation performance corresponding to the identified past transportation conditions.

[0007] Furthermore, the present invention includes a transportation planning step in which a transportation planning unit formulates a transportation plan based on the transportation conditions of the transportation plan to be formulated, past transportation conditions, and the weights of key performance indicators for transportation performance; a key performance indicator estimation step in which an indicator estimation unit calculates the weights of key performance indicators for past transportation conditions by comparing the values ​​of key performance indicators calculated based on the transportation plan formulated by the transportation planning unit with the values ​​of key performance indicators for past transportation performance calculated from past transportation performance; and a key performance indicator setting step in which an indicator setting unit identifies past transportation conditions from among a plurality of past transportation conditions that have the highest similarity to the transportation conditions of the transportation plan to be formulated, and sets the weights of key performance indicators for transportation performance corresponding to the identified past transportation conditions.

[0008] Furthermore, in the present invention, the computer is configured to perform the following steps: a transportation planning step in which a transportation planning unit is instructed to formulate a transportation plan based on the transportation conditions of the transportation plan to be formulated, past transportation conditions, and the weights of key performance indicators for transportation performance; a calculation step in which an indicator estimation unit is instructed to calculate the weights of key performance indicators for past transportation conditions by comparing the values ​​of key performance indicators calculated based on the transportation plan formulated by the transportation planning unit with the values ​​of key performance indicators for past transportation performance calculated from past transportation performance; and a setting step in which an indicator setting unit is instructed to identify the past transportation conditions that are most similar to the transportation conditions of the transportation plan to be formulated from among a plurality of past transportation conditions, and to set the weights of key performance indicators for transportation performance corresponding to the identified past transportation conditions. [Effects of the Invention]

[0009] According to the present invention, a balance can be struck between reducing the number of drivers required and improving the ease of work for drivers, enabling the creation of transportation plans that are favorable to transportation companies and transportation characteristics. [Brief explanation of the drawing]

[0010] [Figure 1] This system configuration diagram shows an example of the hardware configuration of a transportation planning system including a transportation planning device according to this embodiment. [Figure 2] Figure 1 is a system configuration diagram showing an example of the software configuration of a transportation planning system, including the transportation planning device and database device. [Figure 3] This figure shows an example of a function for estimating KPI weights. [Figure 4] This figure shows an example of a function that estimates the weights of KPIs for transportation conditions in the transportation performance data being planned. [Figure 5] This figure shows an example of order information. [Figure 6] This is a diagram showing an example of vehicle information. [Figure 7] This figure shows an example of driver information. [Figure 8]It is a diagram showing an example of KPI weight information. [Figure 9] It is a diagram showing an example of transportation performance information. [Figure 10] It is a diagram showing an example of past transportation condition information. [Figure 11] It is a diagram showing an example of base information. [Figure 12] It is a diagram showing an example of movement information between bases. [Figure 13] It is a flowchart showing an example of the procedure of transportation plan processing. [Figure 14] It is a diagram showing an example of a transportation plan output screen displayed on a display device.

Embodiments for Carrying Out the Invention

[0011] Hereinafter, based on the drawings, an embodiment of the present invention will be described in detail. FIG. 1 is a system configuration diagram showing an example of the hardware configuration of a transportation plan system 1 including a transportation plan device 100 according to this embodiment.

[0012] The transportation plan system 1 includes a transportation plan device 100, at least one vehicle 103, a plan management terminal 102, a database device 104, and a network 101. The transportation plan device 100, at least one vehicle 103, and the plan management terminal 102 are connected to each other via the network 101 and have a function of exchanging data and commands with each other. The vehicle 103 is connected to the network 101, for example, wirelessly. The database device 104 will be described later.

[0013] The transportation plan device 100 is, for example, a computer. The transportation plan device 100 includes a CPU (Central Processing Unit) 21, a RAM (Random Access Memory) 22, a ROM (Read Only Memory) 23, an auxiliary storage device 24, a display device 25, an input device 26, a media reading device 27, and a communication device 28. In the transportation plan device 10, a transportation plan program described later is operating.

[0014] The auxiliary storage device 24 is a large-capacity storage device that stores the transportation plan program non-volatiley in addition to data. The ROM 23 is a storage device that stores data, etc. non-volatiley. The ROM 23 may store the transportation plan program instead of the auxiliary storage device 24.

[0015] The RAM 22 is a volatile storage device that temporarily stores programs such as data and the transportation plan program. The CPU 21 controls the entire transportation planning device 100. The CPU 21 reads the transportation plan program from the auxiliary storage device 24, stores it in the RAM 22, and controls the execution of the transportation plan program. Details of the transportation plan program will be described later.

[0016] The display device 25 is a display device that displays the input and output contents according to the transportation plan program. Examples of the display target by the display device 25 may include the transportation plan output screen described later. The input device 26 is an operation device such as a keyboard and a mouse that receives the input contents from the outside. The media reading device 27 has a function of reading data, etc. from various media. The communication device 28 controls communication with the outside, for example, the vehicle 103, the plan management terminal 102, and the database device 104 via the network 101 under the control of the CPU 21.

[0017] The vehicle 103 starts moving from the first base, stops at at least one base on a predetermined route, and then finally returns to the first base.

[0018] The plan management terminal 102 is arranged at at least one base where the vehicle 103 traveling along a predetermined route stops. The plan management terminal 102 includes a communication device 102A and a display device 102B. The communication device 102A has a function of communicating data and commands with the communication device 28 of the transportation planning device 100 via the network 101. The display device 102B has a function of performing display based on the data, etc. acquired from the transportation planning device 100.

[0019] Figure 2 is a system configuration diagram showing an example of the software configuration of the transportation planning system 1, which includes the transportation planning device 100 and the database device 104 shown in Figure 1. Note that the information held by the database device 104 may instead be held by the transportation planning device 100.

[0020] The transportation planning device 100 is, for example, a computer on which a transportation planning program runs, and includes a transportation planning unit 30, a KPI setting unit 40, and a KPI calculation unit 50. An overview of these transportation planning unit 30, KPI setting unit 40, and KPI calculation unit 50 will be described below.

[0021] The Transportation Planning Department 30 formulates a transportation plan based on the transportation conditions of the transportation plan to be formulated, past transportation conditions, and the weights of KPIs (Key Performance Indicators) as an example of key performance indicators for transportation performance.

[0022] The KPI setting unit 40 is an example of an indicator estimation unit, and it calculates the weight of the KPIs for past transportation conditions by comparing the KPI values ​​calculated based on the transportation plan formulated by the transportation planning unit 30 with the KPI values ​​of past transportation performance calculated from past transportation performance.

[0023] The KPI calculation unit 50 is an example of an indicator estimation unit. It identifies the past transportation conditions that are most similar to the transportation conditions of the transportation plan being formulated from among several past transportation conditions, and sets the weights of the KPIs for the transportation results corresponding to the identified past transportation conditions. Details of the KPI calculation unit 50 will be described later.

[0024] In other words, the above-mentioned transportation planning program, on a computer, executes the following steps: a transportation planning step in which the above-mentioned transportation planning unit 30 formulates a transportation plan based on the transportation conditions of the transportation plan to be formulated, past transportation conditions, and the weights of the KPIs of transportation performance; a calculation step in which the KPI calculation unit 50 calculates the weights of the KPIs for past transportation conditions by comparing the KPI values ​​calculated based on the transportation plan formulated by the transportation planning unit 30 with the KPI values ​​of past transportation performance calculated from past transportation performance; and a setting step in which the KPI setting unit 40 identifies the past transportation conditions that are most similar to the transportation conditions of the transportation plan to be formulated from among a number of past transportation conditions, and sets the weights of the key performance indicators of transportation performance corresponding to the identified past transportation conditions.

[0025] The database device 104 contains order information 107, vehicle information 108, base information 109, driver information 110, transportation performance information 130, and past transportation condition information 140. The database device 104 also contains inter-base travel information, which will be described later. Inter-base travel information is obtained by calculation from at least some combinations of these multiple pieces of information. Details of order information 107, vehicle information 108, base information 109, driver information 110, transportation performance information 130, and past transportation condition information 140 will be described later.

[0026] Figure 3 shows an example of a function for estimating KPI weights. In this embodiment, the appropriate weighting of KPIs for the transportation conditions of the transportation plan to be formulated is unknown and will be determined from scratch. However, it is assumed that there are several transportation performance data 32A to 32E and KPI values ​​for the transportation performance that have been prepared in advance as appropriate KPIs.

[0027] In this embodiment, multiple KPI values ​​33A to 33E for multiple transportation records corresponding to multiple transportation records 32A to 32E, each corresponding to past transportation conditions 31A to 31E, are provided in advance.

[0028] Here, the KPI calculation unit 50 creates a proposed KPI weighting scheme, including the weights 34A to 34E of multiple KPIs, based on the first transportation condition 311A, and inputs it into the transportation planning unit 30.

[0029] The transportation planning unit 30 identifies a transportation plan 35D from among multiple transportation plans 35A to 35E that corresponds to the first transportation condition 311A ​​and a specific KPI weight among the weights of multiple KPIs. The KPI value 36E corresponding to the transportation plan 35D is estimated from among the KPI values ​​36A to 36E.

[0030] The KPI calculation unit 50 estimates the weights of the KPIs for past transportation conditions by comparing the KPI values ​​(for example, KPI value 33A) calculated by the transportation planning unit 30 based on past transportation conditions with the estimated KPI value 36E. The same process is followed for the second transportation condition 312A.

[0031] Figure 4 shows an example of a function for estimating the weights of KPIs for the transportation conditions of the transportation plan being developed. In this embodiment, the appropriate weighting of KPIs for the transportation conditions of the transportation plan being developed is unknown and will be determined from scratch, but it is assumed that there are several pre-prepared transportation records 32A to 32E that are considered to have appropriate KPIs.

[0032] The KPI calculation unit 50 identifies the past transportation condition 31B that has the highest similarity to the transportation condition 31 of the transportation plan being planned, from among the transportation conditions 31A to 31E of multiple transportation plans. The KPI calculation unit 50 identifies the transportation performance 32B that corresponds to the past transportation condition 31B that has the highest similarity, from among the multiple transportation performance 32A to 32E.

[0033] The KPI calculation unit 50 calculates the weights 34A to 34E of multiple KPIs corresponding to the KPI values ​​33A to 33E of multiple transportation records calculated from multiple transportation records 32A to 32E. In the illustrated example, the weights 34A to 34E of multiple KPIs are expressed as the proposed KPI weights 34Z. From the weights 34A to 34E of multiple KPIs included in the proposed KPI weights 34Z, the KPI calculation unit 50 identifies the weight 34B of the KPI for the transportation conditions of the target transportation record that corresponds to the past transportation conditions 31B with the highest similarity, and estimates the weight 34 of the KPI for the transportation conditions of the target transportation record that corresponds to the weight 34B of that KPI.

[0034] This embodiment offers the following advantages over, for example, so-called artificial intelligence in estimating KPI weights. First, estimating KPI weights with artificial intelligence is, in a sense, a black box, and the basis for the estimation is not clear. However, with a method like that of this embodiment, the basis for estimating KPI weights becomes easier to understand. Second, because the similarity of transportation conditions is specifically illustrated, it is possible to prevent the KPI weights from being arbitrarily estimated.

[0035] The transportation planning department 30 formulates a transportation plan based on the weights of the set transportation performance KPIs and the transportation conditions of the transportation plan being planned.

[0036] The transportation planning unit 30 extracts the transportation conditions for the transportation plan to be formulated and the aforementioned past transportation conditions from at least one of the following: order information, vehicle information, driver information, and base information.

[0037] The weights of the KPIs mentioned above include at least one of the following items: minimizing the number of vehicles, minimizing the number of drivers, maximizing the load factor, minimizing the number of violations of collection and delivery time slots, minimizing the number of violations of work time slots, leveling out driver work hours, leveling out the number of visits by drivers, and leveling out the load factor, along with a weight for each of the aforementioned at least one item.

[0038] The KPI setting unit 40 estimates past transportation conditions from past transportation performance. The KPI setting unit 40 determines the similarity of transportation conditions based on, for example, the total number of orders, the total order quantity, the total order quantity relative to the total vehicle load capacity, the length of the order shipping time slot, the length of the order delivery time slot, the distribution of the order shipping time slot, the distribution of the order delivery time slot, the length of the order shipping time slot relative to the length of the vehicle operating time slot, the length of the order delivery time slot relative to the length of the vehicle operating time slot, the length of the order shipping time slot relative to the length of the time required for shipping operations, the length of the order delivery time slot relative to the length of the time required for shipping operations, the number of vehicles, the vehicle load capacity, the length of the vehicle operating time slot, the distribution of the vehicle operating time slot, the number of drivers, the length of the drivers' working time slot, the distribution of the drivers' working time slot, the number of bases, the latitude and longitude of the bases, the distribution of bases, the distance between bases, and the travel time between bases.

[0039] The KPI calculation unit 50 identifies multiple past transportation conditions that are highly similar to the transportation conditions of the transportation plan being formulated, and calculates the weights of the KPIs for the transportation conditions of the transportation plan being formulated by statistically processing the weights of the KPIs for multiple transportation results corresponding to the identified multiple past transportation conditions.

[0040] Figure 5 shows an example of order information 107. Order information 107 manages, for example, the order number, shipping source, delivery destination, quantity, shipping date and time, and delivery date and time. The shipping date and time includes the start date and time and the end date and time. The delivery date and time also includes the start date and time and the end date and time.

[0041] Figure 6 shows an example of vehicle information 108. Vehicle information 108 manages the vehicle name and maximum load capacity for each vehicle 103. Vehicle information 108 may also include other information about each vehicle 103, such as information about the license plate of each vehicle 103, and information indicating whether each vehicle 103 is an electric vehicle, gasoline vehicle, hybrid vehicle, or hydrogen engine vehicle.

[0042] Figure 7 shows an example of driver information 110. Driver information 110 manages, for example, the driver name, the maximum operating time, and the shift. The shift includes the disclosure date and time and the end date and time. Figure 8 shows an example of KPI weight information 120. KPI weight information 120 manages, for example, the weights of items and KPIs.

[0043] Figure 9 shows an example of transportation performance information 130. Transportation performance information 130 manages the date, vehicle name, location name, status, order number, quantity, and time. The time includes the disclosure date and time and the end date and time.

[0044] Figure 10 shows an example of past transportation conditions information 140. Past transportation conditions information 140 manages past transportation conditions. Past transportation conditions information 140 manages, for example, the execution date, items, and conditions.

[0045] Figure 11 shows an example of base information 109. Base information 109 manages information about at least one base where the vehicle 103 is charged. Base information 109 manages, for example, the base, contracted power, and operating hours. Operating hours include the start date and time and the end date and time.

[0046] Figure 12 shows an example of travel information between locations. This travel information manages the departure and arrival locations, travel time, travel distance, and power consumption. The departure and arrival locations include the departure and arrival points of vehicle 103.

[0047] The transportation planning system 1, including the transportation planning device 100 according to this embodiment, has the configuration described above. Next, an example of a transportation planning method using the transportation planning system 1, including the transportation planning device 100, will be described. This transportation planning method includes: a transportation planning step in which the transportation planning unit 30 formulates a transportation plan based on the transportation conditions of the transportation plan to be formulated, past transportation conditions, and the weights of the KPIs of the transportation performance; a calculation step in which the KPI calculation unit 50 calculates the weights of the KPIs for past transportation conditions by comparing the KPI values ​​calculated based on the transportation plan formulated by the transportation planning unit 30 with the KPI values ​​of past transportation performance calculated from past transportation performance; and a setting step in which the KPI setting unit 40 identifies the past transportation conditions that have the highest similarity to the transportation conditions of the transportation plan to be formulated from among a plurality of past transportation conditions, and sets the weights of the KPIs of the transportation performance corresponding to the identified past transportation conditions.

[0048] Figure 13 is a flowchart showing an example of the procedure for transport planning. In step S1, the transport planning device 100 receives transport condition information 140 for which planning is to be made, transport performance information 130, and past transport condition information 140.

[0049] In step S2, the KPI calculation unit 50 formulates a transportation plan based on past transportation condition information and calculates the weights of the KPIs for transportation performance by comparing the KPIs of the formulation result with the KPIs of the transportation performance information. In other words, the KPI calculation unit 50 inputs multiple transportation performance data and past transportation conditions corresponding to each transportation performance, and calculates the weights of the KPIs by comparing the KPIs of the transportation plan formulated based on past transportation conditions with the KPIs of the transportation performance.

[0050] In step S3, the KPI setting unit 40 identifies the past transportation conditions that are most similar to the transportation conditions being planned. In other words, the KPI setting unit 40 identifies the past transportation conditions that are most similar to the transportation conditions being planned and outputs the weights of the KPIs corresponding to those conditions.

[0051] In step S4, the KPI setting unit 40 identifies the weights of the KPIs for transportation performance corresponding to the past transportation conditions identified as described above.

[0052] In step S5, the transportation planning department 30 formulates a transportation plan based on the weights of the above KPIs and the transportation condition information to be planned.

[0053] Figure 14 shows an example of the transportation plan output screen 1000 displayed on the display device 25. The example shown is an output screen for the transportation plan corresponding to the "first transportation plan".

[0054] The transportation plan output screen 1000 includes a delivery schedule display field 1001, a delivery route display field 1002, a similar delivery performance display field 1003, and a KPI display field 1004.

[0055] The delivery schedule display field 1001 displays the delivery schedule. The delivery route display field 1002 displays the delivery route. The delivery route starts from base K0, named "Point 1," passes through bases K1 to K4, and returns to base K0.

[0056] The Similar Delivery History Display field 1003 displays similar delivery history. Similar delivery history refers to past delivery history that is similar to the target delivery history. The KPI Display field 1004 displays KPIs.

[0057] The display device 25 is an example of an output device, and outputs a transportation plan formulated based on the weights of the set KPIs, the transportation conditions of the transportation plan to be formulated, and the weights of the identified KPIs.

[0058] The display device 25 outputs the transportation plan formulated based on the transportation conditions of the transportation plan to be formulated and the weights identified, past transportation records corresponding to transportation conditions that are highly similar to the transportation conditions of the transportation plan to be formulated, and KPI values ​​calculated from past transportation records.

[0059] As described above, the transportation planning system 1 according to this embodiment, which includes the transportation planning unit 30, comprises: a transportation planning unit 30 that formulates a transportation plan based on the transportation conditions of the transportation plan to be formulated, past transportation conditions, and the weights of KPIs as an example of key performance indicators for transportation results; a KPI calculation unit 50 as an example of an indicator estimation unit that calculates the weights of KPIs for past transportation conditions by comparing the KPI values ​​calculated based on the transportation plan formulated by the transportation planning unit 30 with the KPI values ​​of past transportation results calculated from past transportation results; and a KPI setting unit 40 as an example of an indicator setting unit that identifies past transportation conditions that have the highest similarity to the transportation conditions of the transportation plan to be formulated from among a plurality of past transportation conditions, and sets the weights of KPIs for transportation results corresponding to the identified past transportation conditions.

[0060] The transportation planning method according to this embodiment includes: a transportation planning step in which a transportation planning unit 30 formulates a transportation plan based on the transportation conditions of the transportation plan to be formulated, past transportation conditions, and the weights of the KPIs of transportation performance; a calculation step in which a KPI calculation unit 50 calculates the weights of the KPIs for past transportation conditions by comparing the KPI values ​​calculated based on the transportation plan formulated by the transportation planning unit 30 with the KPI values ​​of past transportation performance calculated from past transportation performance; and a setting step in which a KPI setting unit 40 identifies the past transportation conditions that have the highest similarity to the transportation conditions of the transportation plan to be formulated from among a plurality of past transportation conditions, and sets the weights of the KPIs of transportation performance corresponding to the identified past transportation conditions.

[0061] The transportation planning program according to this embodiment executes the following steps on a computer: a transportation planning step in which the above-mentioned transportation planning unit 30 formulates a transportation plan based on the transportation conditions of the transportation plan to be formulated, past transportation conditions, and the weights of the KPIs of the transportation performance; a calculation step in which the KPI calculation unit 50 calculates the weights of the KPIs for past transportation conditions by comparing the KPI values ​​calculated based on the transportation plan formulated by the transportation planning unit 30 with the KPI values ​​of past transportation performance calculated from past transportation performance; and a setting step in which the KPI setting unit 40 identifies the past transportation conditions that have the highest similarity to the transportation conditions of the transportation plan to be formulated from among a plurality of past transportation conditions, and sets the weights of the key performance indicators of transportation performance corresponding to the identified past transportation conditions.

[0062] In this way, a balance can be struck between reducing the number of drivers required and improving the working conditions for drivers (hereinafter referred to as "the balance"), enabling the creation of a transportation plan that is favorable to both the transport company and the transportation characteristics.

[0063] In this embodiment, the transportation planning unit 30 formulates a transportation plan based on the weights of the set transportation performance KPIs and the transportation conditions of the transportation plan to be formulated. In this way, by using the weights of these transportation performance KPIs and the transportation conditions, it is possible to formulate a transportation plan in which the balance is favorable for the transportation company and the transportation characteristics.

[0064] In this embodiment, the transportation planning unit 30 extracts the transportation conditions of the transportation plan to be planned and past transportation conditions from at least one of the following: order information, vehicle information, driver information, and base information. By doing so, it is possible to formulate a transportation plan that is in good balance for the transportation company and transportation characteristics using this information.

[0065] In this embodiment, the weights of the KPIs include at least one of the following items: minimizing the number of vehicles, minimizing the number of drivers, maximizing the load factor, minimizing violations of collection and delivery time slots, minimizing violations of work time slots, leveling out driver work hours, leveling out the number of visits by drivers, and leveling out the load factor, along with a weight for each of the aforementioned at least one item. In this way, by using the at least one item and its corresponding weight, it is possible to formulate a transportation plan in which the balance is good for the transporter and the transportation characteristics.

[0066] In this embodiment, the KPI setting unit 40 estimates past transportation conditions from past transportation performance. In this way, using the estimated past transportation conditions, it is possible to formulate a transportation plan that is favorable for the transportation company and transportation characteristics.

[0067] In this embodiment, the KPI setting unit 40 determines the similarity of transportation conditions based on, for example, the total number of orders, the total order quantity, the total order quantity relative to the total load capacity of the vehicles, the length of the order shipping time slot, the length of the order delivery time slot, the distribution of the order shipping time slots, the distribution of the order delivery time slots, the length of the order shipping time slot relative to the length of the vehicle operating time slot, the length of the order delivery time slot relative to the length of the vehicle operating time slot, the length of the order shipping time slot relative to the length of the time required for shipping operations, the length of the order delivery time slot relative to the length of the time required for shipping operations, the number of vehicles, the load capacity of the vehicles, the length of the vehicle operating time slot, the distribution of the vehicle operating time slot, the number of drivers, the length of the drivers' working time slots, the distribution of the drivers' working time slots, the number of bases, the latitude and longitude of the bases, the distribution of bases, the distance between bases, and the travel time between bases. In this way, according to the determined similarity of transportation conditions, a transportation plan can be formulated in which the balance is good for the transportation company and transportation characteristics.

[0068] The KPI calculation unit 50 identifies multiple past transportation conditions that are highly similar to the transportation conditions of the transportation plan being formulated, and calculates the weights of the KPIs for the transportation conditions of the transportation plan being formulated by statistically processing the weights of the KPIs for multiple transportation results corresponding to the identified multiple past transportation conditions. In this way, using the calculated KPI weights, it is possible to formulate a transportation plan in which the balance is good for the transportation company and the transportation characteristics.

[0069] In this embodiment, the display device 25 is an example of an output device, and outputs a transportation plan formulated based on the set KPI weights, the transportation conditions of the transportation plan to be formulated, and the weights of the identified KPIs. In this way, a transportation plan can be formulated in which the balance between the set KPI weights, the transportation conditions of the transportation plan to be formulated, and the weights of the identified KPIs is favorable for the transportation company and the transportation characteristics.

[0070] In this embodiment, the display device 25 outputs a transportation plan formulated based on the transportation conditions of the transportation plan to be formulated and the weights identified, past transportation records corresponding to transportation conditions with a high degree of similarity to the transportation conditions of the transportation plan to be formulated, and KPI values ​​calculated from past transportation records. In this way, by referring to the output KPI values, it is possible to formulate a transportation plan in which the balance is good for the transportation company and transportation characteristics.

[0071] It should be noted that the present invention is not limited to the embodiments described above, but includes various modifications and equivalent configurations within the spirit of the attached claims. For example, the embodiments described above are described in detail for the purpose of clearly illustrating the present invention, and the present invention is not necessarily limited to having all the configurations described. Also, each element described in parallel in this embodiment may be configured such that at least one of the elements is connected in series with respect to the other elements. [Industrial applicability]

[0072] This invention can be applied to a transportation planning device relating to technology for formulating transportation plans. [Explanation of Symbols]

[0073] 1...Transportation planning system, 30...Transportation planning department, 40...KPI setting department, 50...KPI calculation department, 100...Transportation planning device, 104...Database device

Claims

1. Based on the transportation conditions of the transportation plan to be formulated, past transportation conditions, and the weighting of key performance indicators for transportation performance, the Transportation Planning Department formulates the transportation plan. An indicator estimation unit estimates the weight of key performance indicators for past transportation conditions by comparing the values ​​of key performance indicators calculated based on the transportation plan formulated by the transportation planning unit with the values ​​of key performance indicators for past transportation performance calculated from past transportation performance. An indicator setting unit identifies the past transportation conditions that are most similar to the transportation conditions of the transportation plan being formulated from among multiple past transportation conditions, and sets the weights of key performance indicators for transportation results corresponding to the identified past transportation conditions. A transportation planning device characterized by comprising the following features.

2. The aforementioned transportation planning department, Based on the weights of key performance indicators for established transportation performance and the transportation conditions of the transportation plan being planned, a transportation plan is formulated. The transport planning device according to feature 1.

3. The aforementioned transportation planning department, The transportation conditions of the transportation plan to be planned and the past transportation conditions are extracted from at least one of the following: order information, vehicle information, driver information, and base information. The transport planning device according to feature 1.

4. The weights of the aforementioned key performance indicators are: At least one of the following items: minimizing the number of vehicles, minimizing the number of drivers, maximizing the load factor, minimizing violations of collection and delivery time slots, minimizing violations of work time slots, leveling out driver working hours, leveling out the number of visits by drivers, and leveling out the load factor. The weight for each of the above at least one items, The transport planning device according to claim 1, characterized by including the following:

5. The aforementioned indicator setting unit is The past transportation conditions are estimated from the past transportation records. The transport planning device according to feature 1.

6. The aforementioned indicator setting unit is The similarity of the aforementioned transportation conditions is determined based on at least one of the following: total number of orders, total order quantity, total order quantity relative to the total load capacity of the vehicles, length of the order shipping time slot, length of the order delivery time slot, distribution of the order shipping time slots, distribution of the order delivery time slots, length of the order shipping time slot relative to the length of the vehicle operating time slot, length of the order delivery time slot relative to the length of the vehicle operating time slot, length of the order shipping time slot relative to the length of the time required for shipping operations, length of the order delivery time slot relative to the length of the time required for shipping operations, number of vehicles, vehicle load capacity, length of the vehicle operating time slot, distribution of the vehicle operating time slot, number of drivers, length of the drivers' working time slots, distribution of the drivers' working time slots, number of bases, latitude and longitude of the bases, distribution of bases, distance between bases, and travel time between bases. The transport planning device according to feature 1.

7. The aforementioned index estimation unit, Identify multiple past transportation conditions that are highly similar to the transportation conditions of the transportation plan being considered, and calculate the weights of the key performance indicators for the transportation conditions of the transportation plan being considered by statistically processing the weights of the key performance indicators for multiple transportation records corresponding to the identified multiple past transportation conditions. The transport planning device according to feature 1.

8. The system includes an output device that outputs a transportation plan formulated based on the weights of the set key performance indicators, the transportation conditions of the transportation plan being formulated, and the weights of the identified key performance indicators. The transport planning device according to feature 1.

9. A transportation plan formulated based on the transportation conditions and specified weights of the aforementioned transportation plan subject to formulation, Past transportation records corresponding to transportation conditions that are highly similar to the transportation conditions of the aforementioned transportation plan, The values ​​of key performance indicators calculated from the aforementioned past transportation performance, It is equipped with an output device that outputs an output. The transport planning device according to feature 1.

10. The Transportation Planning Department formulates a transportation plan based on the transportation conditions of the transportation plan under consideration, past transportation conditions, and the weighting of key performance indicators for transportation performance. The calculation step involves the indicator estimation unit comparing the values ​​of key performance indicators calculated based on the transportation plan formulated by the transportation planning unit with the values ​​of key performance indicators for past transportation performance calculated from past transportation performance to calculate the weights of key performance indicators for past transportation conditions, The indicator setting unit identifies the past transportation conditions that are most similar to the transportation conditions of the transportation plan being formulated from among multiple past transportation conditions, and sets the weights of key performance indicators for transportation results corresponding to the identified past transportation conditions. A transportation planning method characterized by having the following features.

11. The transportation planning department is instructed to formulate a transportation plan based on the transportation conditions of the transportation plan to be formulated, past transportation conditions, and the weighting of key performance indicators for transportation performance. A calculation step involves having the indicator estimation unit calculate the weight of the key performance indicators for past transportation conditions by comparing the values ​​of key performance indicators calculated based on the transportation plan formulated by the transportation planning unit with the values ​​of key performance indicators for past transportation performance calculated from past transportation performance. The indicator setting unit includes a setting step of identifying the past transportation conditions that are most similar to the transportation conditions of the transportation plan being formulated from among multiple past transportation conditions, and setting the weights of key performance indicators for transportation results corresponding to the identified past transportation conditions. A computer-readable transportation planning program characterized by its ability to execute.

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