High-speed rail emergency train number matching optimization method and system based on timeliness guarantee

Abstract

The invention provides a high-speed rail emergency train number matching optimization method and system based on timeliness guarantee, and belongs to the field of logistics distribution scheme optimization. According to the method, the set business process comprises customer delivery, goods pickup and delivery, inter-station transportation and goods pickup and delivery; according to the order data and the rider data, the taking and delivering service time distribution of the two links of taking goods to the station and taking goods and delivering goods is constructed, and then the goods waiting time, the latest arrival time of the day and the goods arrival time meeting the maximum delay time are determined; taking the smaller value of the latest arrival time of the day and the cargo arrival time meeting the maximum delay time as the latest arrival time of the cargo; determining a train alternative set according to cargo time limit requirements and cargo OD stations; and based on the timeliness guarantee and the operation cost, constructing a high-speed rail emergency train number matching optimization model based on the timeliness guarantee, and solving the model to obtain an optimized train number matching result. According to the invention, the punctuality and reliability of transportation are improved, and the overall operation efficiency and economic benefits are improved.

Description

Technical Field

[0001] The present invention belongs to the field of optimizing logistics distribution solutions, and particularly relates to a method and system for optimizing the train number matching of high-speed rail express delivery based on timeliness guarantee. Background Art

[0002] With the rapid development of e-commerce and new Internet technologies, the demand for high-efficiency logistics services such as instant delivery and same-day delivery has been increasing day by day, promoting the continuous enrichment and improvement of the fast logistics system, and effectively ensuring the smooth circulation between production and consumption. In the past decade, not only has the total demand for fast logistics continued to grow, but consumers' requirements for logistics timeliness have also become higher and higher. The proportion of high-timeliness express delivery demand has gradually increased, and each express delivery enterprise has successively launched products such as express delivery within the hour, same-day delivery, and next-morning delivery to meet people's diverse needs. In the trunk transportation of high-timeliness express delivery, high-speed railways have received great attention from the government, enterprises, and society due to their advantages such as developed networks, high speeds, high reliability, and environmental friendliness.

[0003] Among them, high-speed rail express delivery based on high-speed railway transportation is a new type of logistics product for cross-city instant delivery, providing more diverse services. The high-speed rail express delivery product uses high-speed rail EMU trains as the main transportation force, and at the same time can connect the pick-up and delivery riders in the same city at both ends, providing a "door-to-door" same-day delivery service that can achieve instant response across cities (across provinces). According to the order information, pick-up / delivery time within the city, and high-speed rail transportation resource situation, the optimal high-speed rail transportation resources are planned and matched for the goods. Reasonable train number matching is of great significance for improving transportation timeliness, reducing operating costs, and improving the utilization rate of transportation resources.

[0004] In the prior art, in the station cargo transportation link of high-speed rail express delivery, train number matching mainly relies on manual operation by station staff. After the goods are delivered to the station, the staff select appropriate high-speed rail trains to transport the goods based on experience and limited information. However, this method not only has low efficiency, consumes a large amount of human and time resources, but also is difficult to ensure the efficient utilization of train transport capacity. At the same time, the time constraint conditions of the goods cannot be fully considered during the manual screening process, resulting in some goods may be detained at the station for a long time due to improper train number selection, seriously affecting the transportation timeliness. In addition, the existing train number matching process views the transportation arrangements of each batch of goods in isolation, without comprehensively considering the transportation benefits from the perspective of the overall transportation network, which is not conducive to improving the overall operation efficiency and economic benefits of high-speed rail express delivery, and is also difficult to cope with the future growing business volume and complex and changeable market demands. Although some scholars have given improvement measures for high-speed rail express delivery methods, there are still certain deficiencies. For example, current domestic and foreign scholars' research on cargo transportation plans mostly focuses on the problem of minimizing transportation costs, but ignores the overall consideration of the timeliness of the entire process covering multiple links of front-end and back-end transportation and main-line transportation. The existing optimization of train number matching only considers deterministic or uncertain cargo demands, but ignores the uncertainty of front-end and back-end transportation times. In actual operation, factors such as urban traffic congestion and weather changes will make it difficult to accurately estimate the pick-up and delivery times, which directly affects the matching degree of train numbers and cargo transportation times, easily leading to goods waiting at the station for a long time or delaying transportation, and reducing the overall transportation efficiency. Summary of the Invention

[0005] In view of the above defects or deficiencies in the prior art, the present invention aims to provide an optimization method and system for high-speed rail express train number matching based on timeliness guarantee, which matches the pick-up and delivery of front-end and back-end of order goods, and encapsulates the front-end and back-end pick-up and delivery matching module, cargo time limit requirement calculation module, train alternative set determination module, and train number matching optimization module in the optimization process into a system, which can realize the train number matching of goods from scratch.

[0006] To achieve the above object, the embodiments of the present invention adopt the following technical solutions:

[0007] In the first aspect, the embodiments of the present invention provide an optimization method for high-speed rail express train number matching based on timeliness guarantee, and the method includes the following steps:

[0008] Step S1, set the business process of high-speed rail express delivery to include customer shipping, pick-up and loading onto the station, inter-station transportation, and delivery and distribution; pick-up and loading onto the station is the front end of inter-station transportation, and delivery and distribution is the back end of inter-station transportation;

[0009] Step S2, construct the pick-up and delivery service time distribution of the two links of pick-up and loading onto the station and delivery and distribution according to the order data and rider data;

[0010] Step S3: Determine the waiting time for goods transportation and the latest arrival time at the station for same-day delivery based on the pick-up and delivery service time distribution, station operation time, customer appointment time, and the latest time to deliver goods to the customer on the same day;

[0011] Step S4: Obtain the penalty duration of the goods and the arrival time of the goods meeting the maximum delay time based on the train timetable, waiting time for goods transportation, delay limit, and order data;

[0012] Step S5: Take the smaller value between the latest arrival time at the station for same-day delivery and the arrival time of the goods meeting the maximum delay time as the latest arrival time of the goods;

[0013] Step S6: Determine the train alternative set for the goods according to the time limit requirements of the goods and the origin-destination (OD) stations of the goods; the time limit requirements include that the waiting time for goods transportation should be earlier than the departure time of the train at the departure station, and at the same time, the latest arrival time of the goods should be later than the arrival time of the train at the destination station;

[0014] Step S7: Based on timeliness guarantee and train operation cost, construct an optimization model for high-speed rail urgent delivery train number matching based on timeliness guarantee; the constraint conditions of the objective function in the optimization model include train stop constraints, train loading capacity constraints, total cargo volume constraints, and train alternative set constraints;

[0015] Step S8: Solve the optimization model for high-speed rail urgent delivery train number matching based on timeliness guarantee to obtain the optimized train number matching for high-speed rail urgent delivery orders.

[0016] As a preferred embodiment of the present invention, the waiting time for goods transportation in Step S3 includes two stages: pick-up and station operation, which is calculated from three parts: customer appointment time, pick-up time by the rider to the station, and station operation time; the latest arrival time at the station for same-day delivery includes two stages: station operation and delivery, which is calculated from three parts: the latest time to deliver goods to the customer on the same day, delivery time by the rider, and station operation time.

[0017] As a preferred embodiment of the present invention, Step S4 to determine the arrival time of the goods meeting the maximum delay time specifically includes the following steps:

[0018] Step S41: Calculate the benchmark value of the penalty duration between stations according to the train timetable;

[0019] Step S42: Calculate the penalty duration of the goods by combining the benchmark value of the penalty duration, waiting time for goods transportation, OD stations of the goods, and the arrival time of the train at the destination station of the goods;

[0020] Step S43: Calculate the arrival time of the goods meeting the maximum delay time by combining the benchmark value of the penalty duration, waiting time for goods transportation, OD stations of the goods, and delay limit.

[0021] As a preferred embodiment of the present invention, when constructing the pick-up and delivery service time distribution in step S2, it is assumed that the pick-up and delivery times of the front and rear riders follow a normal distribution N(μ,σ 2 ), where the expected value is calculated based on the distance between the user and the station and the average speed of the rider;

[0022] Construct the pick-up and delivery service time distributions at the front and rear ends as follows:

[0023]

[0024] In formulas (1)-(2), Q represents the set of high-speed rail express orders, q represents the order index, and q ∈ Q; represents the time when the rider of order q picks up the goods and arrives at the station; represents the time when the rider of order q delivers the picked-up goods; represents the distance from which the rider of order q picks up the goods, in km; represents the distance for the rider of order q to deliver the picked-up goods, in km; v represents the average speed of the rider for pick-up and delivery at both ends, in km / h; σ is the time unit, and the pick-up and delivery times of the front and rear riders are within the interval (-2σ, 3σ).

[0025] As a preferred embodiment of the present invention, the formulas for determining the time when the goods are waiting to be transported and the time when the goods arrive at the station to meet the same-day delivery requirement are as follows:

[0026]

[0027] In formulas (3)-(4), represents the time when the goods of order q are waiting to be transported; represents the time when the goods of order q arrive at the station to meet the same-day delivery requirement; represents the customer appointment time of order q; represents the latest time to deliver the goods to the customer of order q; t r represents the station operation time.

[0028] As a preferred embodiment of the present invention, in step S41, the average value of the running duration between the OD stations of the goods is used as the penalty duration reference value:

[0029]

[0030] In formula (5), K represents the set of trains, k represents the train index, and k ∈ K; N represents the set of stations, i, j represent the station indices, i, j ∈ N, and (i, j) represents the set of station intervals; represents the penalty duration reference value for the interval (i, j), in min; T k (i, j) represents the running duration of train k in the interval (i, j), in min; Denote a 0-1 variable, whose value is 1 indicating that train k stops at station i and station i meets the freight operation requirements; otherwise, its value is 0. Denote a 0-1 variable, whose value is 1 indicating that train k stops at station j and station j meets the freight operation requirements; otherwise, its value is 0.

[0031] In step S42, the penalty duration calculation formula:

[0032]

[0033] In formula (6), Δt k,q represents the penalty duration for order q to select train k; i q represents the departure station of order q; j q represents the destination station of order q; represents the arrival time of train k at station j q of;

[0034] In step S43, the calculation method for the arrival time of goods meeting the maximum delay time is:

[0035]

[0036] In formula (7), represents the arrival time of goods of order q meeting the maximum delay time; Δh(q) represents the delay time limit of order q.

[0037] As a preferred embodiment of the present invention, the calculation method for determining the train alternative set is:

[0038]

[0039] In formulas (9)-(10), represents whether train k meets the requirement that the waiting time of the goods of order q is earlier than the departure time of the train at the departure station, taking 1 if it meets, and 0 if it does not meet; represents whether train k meets the requirement that the latest arrival time of the goods of order q is later than the arrival time of the train at the destination station, taking 1 if it meets, and 0 if it does not meet; β k,q represents whether train k meets the time limit requirement of order q, taking 1 if it meets, and 0 if it does not meet; represents train k at station i q of the departure time; M represents a number much larger than other parameters.

[0040] As a preferred embodiment of the present invention, the objective function in step S7 is:

[0041]

[0042] In formula (11), x k,qIndicate whether the goods of order q are transported by train with train number k. If selected, take 1; if not selected, take 0; c f Indicate the time penalty coefficient of unit containerized unit goods, with the unit of yuan / containerized unit·min; c k Indicate the unit distance cost of transporting unit containerized unit goods by the corresponding train, with the unit of yuan / containerized unit·km; l(i q ,j q ) Indicate the distance of the section (i q ,j q ) in km; n q Indicate the quantity of goods corresponding to order q.

[0043] As a preferred embodiment of the present invention, in step S8, the Gurobi solver is used to solve the train number matching optimization model.

[0044] In a second aspect, an embodiment of the present invention further provides a high-speed rail express train number matching optimization system based on timeliness guarantee. The system includes: a business division module, a front-end and back-end service time calculation module, a goods waiting time calculation module, a goods latest time determination module, a train alternative set construction module, a train number matching optimization model construction module, and a matching result output module; among them,

[0045] The business division module is used to set the business process of high-speed rail express, including customer shipping, pick-up and loading at the station, inter-station transportation, and delivery and pick-up; pick-up and loading at the station is the front end of inter-station transportation, and delivery and pick-up is the back end of inter-station transportation;

[0046] The front-end and back-end service time calculation module is used to construct the pick-up and delivery service time distribution of the two links of pick-up and loading at the station and delivery and pick-up according to order data and rider data;

[0047] The goods waiting time calculation module is used to determine the goods waiting time according to the pick-up and delivery service time distribution, station operation time, customer appointment time, and the latest time to be delivered to the customer on the same day;

[0048] The goods latest time determination module is used to determine the latest arrival time at the station for same-day delivery according to the pick-up and delivery service time distribution, station operation time, customer appointment time, and the latest time to be delivered to the customer on the same day; it is also used to obtain the penalty duration of the goods and the arrival time of the goods that meet the maximum delay time according to the train timetable, goods waiting time, delay limit, and order data; and it is used to take the smaller value of the latest arrival time at the station for same-day delivery and the arrival time of the goods that meet the maximum delay time as the latest arrival time of the goods;

[0049] The train alternative set construction module is used to determine the train alternative set of the goods according to the time limit requirements of the goods and the OD stations of the goods; the time limit requirements include that the waiting time of the goods should be earlier than the departure time of the train at the departure station, and at the same time, the latest arrival time of the goods should be later than the arrival time of the train at the destination station;

[0050] The train number matching optimization model construction module is used to construct a high-speed rail express train number matching optimization model based on timeliness guarantee and train operation cost; the constraint conditions of the objective function in the optimization model include train stop constraints, train loading capacity constraints, total cargo volume constraints, and train alternative set constraints;

[0051] The matching result output module is used to solve the high-speed rail express train number matching optimization model based on timeliness guarantee, and obtain and output the train number matching result of the optimized high-speed rail express order.

[0052] The technical solution provided by the embodiment of the present invention has the following beneficial effects:

[0053] The high-speed rail express train number matching optimization method and system based on timeliness guarantee provided by this embodiment can quickly and accurately perform train number matching in an automated and intelligent manner, greatly improving work efficiency and the utilization rate of train transport capacity; with timeliness guarantee as the core, fully considering various time factors, ensuring that goods can be delivered within the specified time, and improving the punctuality and reliability of transportation; comprehensively considering transportation benefits from the perspective of the overall transportation network, optimizing train number matching, enhancing the overall operation efficiency and economic benefits, and strengthening the ability of high-speed rail express to respond to market changes.

[0054] Of course, it is not necessary for any product or method implementing the present invention to achieve all the above-mentioned advantages simultaneously. Description of the Drawings

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0056] Figure 1 It is the flowchart of the high-speed rail express train number matching optimization method based on timeliness guarantee described in the embodiment of the present invention;

[0057] Figure 2 It is the business process description diagram in the embodiment of the present invention;

[0058] Figure 3 It is the schematic diagram of penalty time calculation principle in the embodiment of the present invention. Detailed Embodiments

[0059] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and illustrated in the drawings here can be arranged and designed in various different configurations. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can also be combined with each other.

[0060] It should be noted that similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. In the description of the present invention, the terms "first", "second", "third", "fourth", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0061] For the logistics service of the high-speed rail express delivery type of the present invention, an optimization method and system for matching high-speed rail express delivery train numbers based on timeliness guarantee are proposed. Based on the entire process of the high-speed rail express delivery service, combined with high-speed rail express delivery order data, train timetables, and station operation requirements, front-end and back-end pick-up and delivery matching are performed to determine the time limit requirements of the goods. Further, according to the time limit requirements of the goods and the OD stations of the goods, a set of alternative trains that can transport the goods is screened out; the matching of high-speed rail express delivery train numbers is optimized by comprehensively considering the timeliness guarantee of the goods and the train operation cost, and the matching of the train numbers of the optimized high-speed rail express delivery orders is obtained. By efficiently and accurately matching reasonable train numbers for each batch of high-speed rail express delivery order goods, the present invention can improve the transportation efficiency while ensuring the timeliness and economy of transportation.

[0062] As Figure 1 shown, the optimization method for matching high-speed rail express delivery train numbers based on timeliness guarantee includes the following steps:

[0063] Step S1, set the business process of high-speed rail express delivery to include customer shipping, pick-up and loading onto the station, inter-station transportation, and delivery and distribution.

[0064] In this step, the business process may further include after-sales service.

[0065] Step S2, construct the time distribution of pick-up and delivery services for the two links of pick-up and loading onto the station and delivery and distribution according to the order data and rider data.

[0066] In this step, as Figure 2 shown, take the pick-up and loading onto the station as the front end and the delivery and distribution as the back end. Since there are fluctuations and uncertainties in time in the pick-up and delivery situations of riders at the front and back ends, in order to ensure the reliability and flexibility of the pick-up and delivery service time at the front and back ends, it is considered that the pick-up and delivery times of riders at the front and back ends follow a normal distribution N(μ,σ 2) where the expected value can be calculated based on the distance between the user and the station and the average speed of the rider; based on this, the pick-up and delivery service time distributions at the front and back ends are constructed:

[0067]

[0068] In formulas (1)-(2), Q represents the set of high-speed rail express orders, q represents the order index, and q ∈ Q; represents the time for the rider of order q to pick up the goods and arrive at the station; represents the time for the rider of order q to pick up the goods and deliver them; represents the distance for the rider of order q to pick up the goods and arrive at the station, in km; represents the distance for the rider of order q to pick up the goods and deliver them, in km; v represents the average speed of the rider for pick-up and delivery at both ends, in km / h.

[0069] The pick-up and delivery times of the rider at both ends are set within the interval (-2σ, 3σ) to ensure that the pick-up and delivery times of the rider at both ends calculated satisfy the actual situation with a high probability.

[0070] Step S3, determine the waiting time for the goods to be transported and the latest arrival time at the station for same-day delivery according to the pick-up and delivery service time distribution, the station operation time, the customer appointment time, and the latest time to deliver the goods to the customer on the same day.

[0071] In this step, the waiting time for the goods to be transported refers to the moment when the goods are delivered to the departure station and completed with station operations such as packing and handling, and then start waiting for the train. The specific process can be described in two stages: picking up the goods and arriving at the station, and station operations, which are calculated from three parts: the customer appointment time, the time for the rider to pick up the goods and arrive at the station, and the station operation time; the arrival time of the goods at the station required to meet the same-day delivery need refers to the time when the goods need to arrive at the destination station when they are delivered to the customer at the latest on the same day. The specific process can be described in two stages: station operations and picking up the goods and delivering them, which are calculated from three parts: the latest time to deliver the goods to the customer on the same day, the time for the rider to pick up the goods and deliver them, and the station operation time; comprehensively consider multiple time factors to perform pick-up and delivery matching at the front and back ends to determine the waiting time for the goods to be transported and the arrival time of the goods at the station required to meet the same-day delivery need:

[0072]

[0073] In formulas (3)-(4), represents the waiting time for the goods to be transported for order q; represents the arrival time of the goods at the station required to meet the same-day delivery need for order q; represents the customer appointment time for order q; represents the latest time to deliver the goods to the customer on the same day for order q; t r represents the station operation time.

[0074] Step S4: Obtain the penalty duration of the goods and the arrival time of the goods that meets the maximum delay time based on the train timetable, the time when the goods are waiting to be transported, the delay limit, and the order data.

[0075] In this step, as Figure 3 shown, to determine the arrival time of the goods that meets the maximum delay time, the specific steps are as follows:

[0076] Step S41: Calculate the penalty duration benchmark value between each pair of stations according to the train timetable.

[0077] In this step, the penalty duration benchmark value refers to that due to different train running speeds and stop station plans, trains between the same OD stations have different running durations, and thus the goods have different in-transit durations when carried on different trains. The average value of the running durations of the passenger-carrying multiple units that meet the freight operation conditions between the goods OD stations is used as the penalty duration benchmark value:

[0078]

[0079] In formula (5), K represents the set of trains, k represents the train index, k ∈ K; N represents the set of stations, i, j represent the station indexes, i, j ∈ N, and (i, j) represents the set of station intervals; represents the penalty duration benchmark value of the interval (i, j), with the unit of min; T k (i, j) represents the running duration of train k in the interval (i, j), with the unit of min; represents a 0-1 variable, whose value is 1 indicating that train k stops at station i and station i meets the freight operation requirements, otherwise, its value is 0; represents a 0-1 variable, whose value is 1 indicating that train k stops at station j and station j meets the freight operation requirements, otherwise, its value is 0.

[0080] Step S42: Calculate the penalty duration of the goods by combining the penalty duration benchmark value, the time when the goods are waiting to be transported, the goods OD stations, and the arrival time of the train at the goods destination station.

[0081] In this step, the penalty duration refers to that if the sum of the delay duration caused by the goods waiting for the train at the station and the in-transit duration after boarding the train is greater than the penalty duration benchmark value, the difference from the benchmark value is the penalty duration; if the sum is less than the benchmark value, the penalty duration is 0 and no penalty fee is generated; based on this, a penalty duration calculation formula is constructed:

[0082]

[0083] In formula (6), Δt k,q represents the penalty duration for order q to select train k; i q represents the departure station of order q; jq Denotes the destination station of order q; Denotes that train k is at station j q The arrival time at the station.

[0084] Step S43: Calculate the arrival time of the goods that meets the maximum delay time by combining the penalty duration reference value, the goods waiting time for shipment, the goods OD stations, and the delay limit.

[0085] In this step, the arrival time of the goods that meets the maximum delay time refers to the time when the ordered goods arrive at the destination station after the maximum delay time after waiting for shipment at the departure station. The sum of the penalty duration reference value and the delay limit is the maximum delay time. And when the user selects different urgent delivery types (fastest speed / highest cost performance), the delay limit of the goods is different. Therefore, the calculation method for the arrival time of the goods that meets the maximum delay time is as follows:

[0086]

[0087] In formula (7), Denotes the arrival time of the goods of order q that meets the maximum delay time; Δh(q) denotes the delay limit of order q.

[0088] Step S5: Take the smaller value between the latest arrival time for same-day delivery and the arrival time of the goods that meets the maximum delay time as the latest arrival time of the goods.

[0089] In this step, the latest arrival time of the goods is the time when the goods are delivered to the destination station at the latest, taking the minimum value of the arrival time of the goods required for same-day delivery and the arrival time of the goods that meets the maximum delay time. Therefore, the calculation method for the latest arrival time of the goods is as follows:

[0090]

[0091] In formula (8), Denotes the latest arrival time of the goods of order q.

[0092] Step S6: Determine the alternative set of trains for the goods according to the time limit requirements of the goods and the origin-destination (OD) stations of the goods (origin - destination).

[0093] In this step, the time limit requirements include that the waiting time for shipment of the goods should be earlier than the departure time of the train at the departure station, and at the same time, the latest arrival time of the goods should be later than the arrival time of the train at the destination station. Considering the trains used to transport the goods, they must handle passenger transportation services at the OD stations of the goods and are all arranged to stop. Thus, the calculation method for determining the alternative set of trains is as follows:

[0094]

[0095] In formulas (9)-(10), indicates whether the waiting time for the goods of order q by train k is earlier than the departure time of the train at the departure station. If it is satisfied, take 1; if not, take 0; indicates whether the latest arrival time of the goods of order q by train k is later than the arrival time of the train at the destination station. If it is satisfied, take 1; if not, take 0; β k,q indicates whether train k meets the time limit requirement of order q. If it is satisfied, take 1; if not, take 0; indicates the departure time of train k at station i q ; M represents a number much larger than other parameters. Here, M is a sufficiently large real number, exceeding other parameters by three orders of magnitude.

[0096] Step S7. Based on timeliness guarantee and train operation cost, construct an optimized model for matching high-speed rail express train numbers based on timeliness guarantee.

[0097] In this step, the construction of the optimized model for matching high-speed rail express train numbers based on timeliness guarantee specifically includes:

[0098] Step S71. Take the minimum total cost of high-speed rail express cargo transportation as the objective function, including the time penalty cost caused by cargo delay and the operation cost of the train. The objective function is:

[0099]

[0100] In formula (11), x k,q indicates whether the goods of order q choose the train with train number k for transportation. If it is selected, take 1; if not, take 0; c f indicates the time penalty coefficient per unit containerized unit of goods, with the unit of yuan / containerized unit·min; c k indicates the unit distance cost of transporting a unit containerized unit of goods by the corresponding train, with the unit of yuan / containerized unit·km; l(i q ,j q ) represents the distance of the interval (i q ,j q )), with the unit of km; n q indicates the quantity of goods corresponding to order q.

[0101] Step S72. Establish the train stop constraint of the objective function.

[0102] In this step, the prerequisite for a high-speed rail station to undertake express business is that the train stops at the station and the station facilities meet the operation requirements. The train stop constraint function is:

[0103]

[0104] Step S73: Establish the train loading capacity constraint for the objective function.

[0105] In this step, the cargo loading capacity of each train within any adjacent station section is less than the cargo capacity of the train. The train loading capacity constraint function is as follows:

[0106]

[0107] In Equation (13), H represents the set of sections between adjacent stations on the high - speed rail line, h represents the section index between adjacent stations on the high - speed rail line, h ∈ H; ω(h, q) represents whether the OD station section of order q contains section h, taking 1 if it contains and 0 if it does not; P represents the cargo capacity of the train, with the unit of container unit.

[0108] Step S74: Establish the total cargo quantity constraint.

[0109] In this step, for the same - day delivery goods carried by high - speed rail express, it is necessary to ensure that they are delivered to the destination on the same day, that is, each order will definitely be transported by a train on the same day. The total cargo quantity constraint function is as follows:

[0110]

[0111] Step S75: Establish the train alternative set constraint.

[0112] In this step, the cargo can only be selected on the trains within its train alternative set. The train alternative set constraint function is as follows:

[0113]

[0114] Step S8: Solve the high - speed rail express train number matching optimization model based on timeliness guarantee to obtain the optimized train number matching for high - speed rail express orders.

[0115] In this step, the Gurobi solver is used to solve the train number matching optimization model.

[0116] Using the method of this embodiment, a case is generated with the train timetable of the national high - speed rail line and the assumed high - speed rail express order data, including 76 same - day delivery orders and 55 passenger - carrying multiple - unit trains. The solution results show that the total cost is 41024.07 yuan, ensuring the effective delivery of goods and verifying the effectiveness of the model and the system.

[0117] Based on the same idea, the embodiment of the present invention also provides a high - speed rail express train number matching optimization system based on timeliness guarantee. The system includes:

[0118] The system includes: a business division module, a front-end and back-end service time calculation module, a goods waiting time calculation module, a latest goods time determination module, a train alternative set construction module, a train number matching optimization model construction module, and a matching result output module; among which,

[0119] The business division module is used to set the business process of high-speed rail express delivery, including customer shipment, pick-up and station loading, inter-station transportation, and delivery and pick-up; pick-up and station loading is the front end of inter-station transportation, and delivery and pick-up is the back end of inter-station transportation;

[0120] The front-end and back-end service time calculation module is used to construct the pick-up and delivery service time distribution for the two links of pick-up and station loading and delivery and pick-up according to order data and rider data;

[0121] The goods waiting time calculation module is used to determine the goods waiting time according to the pick-up and delivery service time distribution, station operation time, customer appointment time, and the latest time to be delivered to the customer on the same day;

[0122] The latest goods time determination module is used to determine the latest arrival time of the same-day delivery according to the pick-up and delivery service time distribution, station operation time, customer appointment time, and the latest time to be delivered to the customer on the same day; it is also used to obtain the penalty duration of the goods and the arrival time of the goods that meet the maximum delay time according to the train timetable, goods waiting time, delay limit, and order data; and it is used to take the smaller value of the latest arrival time of the same-day delivery and the arrival time of the goods that meet the maximum delay time as the latest arrival time of the goods;

[0123] The train alternative set construction module is used to determine the train alternative set of the goods according to the goods time limit requirements and the OD stations of the goods; the time limit requirements include that the waiting time of the goods should be earlier than the departure time of the train at the departure station, and at the same time, the latest arrival time of the goods should be later than the arrival time of the train at the destination station;

[0124] The train number matching optimization model construction module is used to construct a high-speed rail express train number matching optimization model based on timeliness guarantee and train operation cost; the constraint conditions of the objective function in the optimization model include train stop constraints, train loading capacity constraints, total goods volume constraints, and train alternative set constraints;

[0125] The matching result output module is used to solve the high-speed rail express train number matching optimization model based on timeliness guarantee, and obtain and output the train number matching result of the optimized high-speed rail express order.

[0126] In this embodiment, each module is implemented by a processor, and a memory is appropriately added when storage is required. Among them, the processor may be, but is not limited to, a microprocessor MPU, a central processing unit (CPU), a network processor (NP), a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), other programmable logic devices, discrete gate, transistor logic devices, discrete hardware components, etc. The memory may include a random access memory (RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory. Optionally, the memory may also be at least one storage device located far from the aforementioned processor.

[0127] In the above embodiment, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.).

[0128] In addition, it should be noted that the high-speed rail express train number matching optimization system based on timeliness guarantee described in this embodiment corresponds to the high-speed rail express train number matching optimization method based on timeliness guarantee. The description and limitation of the method also apply to the system, and will not be repeated here.

[0129] The above description is only a preferred embodiment of the present invention and an explanation of the applied technical principles, and is not intended to limit the scope of the present invention claimed, but only represents the preferred embodiments of the present invention. Those skilled in the art should understand that the scope of the invention involved in the present invention is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

Claims

1. An optimized method for matching high-speed rail emergency delivery train numbers based on time-limit guarantee, characterized in that, The method includes the following steps: Step S1, set the business process of high-speed rail express delivery to include customer shipping, pick-up and station loading, inter-station transportation, and delivery and pick-up; pick-up and station loading is the front end of inter-station transportation, and delivery and pick-up is the back end of inter-station transportation; Step S2, according to the order data and rider data, construct the pick-up and delivery service time distribution for the two links of pick-up and station loading and delivery and pick-up; Step S3, according to the pick-up and delivery service time distribution, station operation time, customer appointment time, and the latest time to deliver to the customer on the same day, determine the waiting time for the goods to be transported and the latest arrival time at the station on the same day; Step S4, according to the train timetable, waiting time for the goods to be transported, delay limit, and order data, obtain the penalty duration of the goods and the arrival time of the goods that meets the maximum delay time; Step S5, take the smaller value between the latest arrival time at the station on the same day and the arrival time of the goods that meets the maximum delay time as the latest arrival time of the goods; Step S6, determine the train alternative set for the goods according to the time limit requirements of the goods and the origin-destination (OD) stations of the goods; the time limit requirements include that the waiting time for the goods should be earlier than the departure time of the train at the departure station, and at the same time, the latest arrival time of the goods should be later than the arrival time of the train at the destination station; Step S7, based on timeliness guarantee and train operation cost, construct an optimization model for high-speed rail express train number matching based on timeliness guarantee; the constraint conditions of the objective function in the optimization model include train stop constraints, train loading capacity constraints, total cargo volume constraints, and train alternative set constraints; Step S8, solve the optimization model for high-speed rail express train number matching based on timeliness guarantee to obtain the train number matching of the optimized high-speed rail express order.

2. The method according to claim 1, wherein The waiting time for the goods to be transported in Step S3 includes two stages: pick-up and station loading and station operation, which is calculated from three parts: the customer appointment time, the time for the rider to pick up and load at the station, and the station operation time; the latest arrival time at the station on the same day includes two stages: station operation and delivery and pick-up, which is calculated from three parts: the latest time to deliver to the customer on the same day, the time for the rider to pick up and deliver the goods, and the station operation time.

3. The method according to claim 1, wherein Step S4 determines the arrival time of the goods that meets the maximum delay time, specifically including the following steps: Step S41, calculate the penalty duration benchmark value for each inter-station according to the train timetable; Step S42, combine the penalty duration benchmark value, waiting time for the goods to be transported, OD stations of the goods, and the arrival time of the train at the destination station of the goods to calculate the penalty duration of the goods; Step S43, combine the penalty duration benchmark value, waiting time for the goods to be transported, OD stations of the goods, and the delay limit to calculate the arrival time of the goods that meets the maximum delay time.

4. The method according to any one of claims 1 to 3, characterized in that When constructing the pick-up and delivery service time distribution in step S2, it is assumed that the pick-up and delivery times of the front and rear riders follow a normal distribution N(μ,σ 2 ), where the expected value is calculated based on the distance between the user and the station and the average speed of the rider; Construct the pick-up and delivery service time distribution for the front and back ends as follows: In formulas (1)-(2), Q represents the set of high-speed rail express delivery orders, q represents the order index, and q ∈ Q; represents the time when the rider of order q picks up the goods at the starting station; represents the time when the rider of order q delivers the goods after picking them up; represents the distance from the starting station where the rider of order q picks up the goods, in km; represents the distance that the rider of order q travels to deliver the goods after picking them up, in km; v represents the average speed of the rider for pick-up and delivery at both ends, in km / h; σ is the time unit, and the pick-up and delivery times of the riders at both ends are within the interval of (-2σ, 3σ).

5. The method according to claim 4, wherein The formulas for determining the waiting time for the goods to be transported and the arrival time of the goods that meets the same-day delivery requirement are as follows: In formulas (3)-(4), represents the time when the goods of order q are ready for shipment; represents the arrival time of the goods of order q required to meet the same-day delivery; represents the customer appointment time of order q; represents the latest time to deliver to the customer for order q; t r represents the station operation time.

6. The method according to claim 5, characterized in that In Step S41, the average value of the running duration between the OD stations of the goods is used as the penalty duration benchmark value: In Equation (5), \(K\) represents the set of trains, \(k\) represents the train index, \(k\in K\); \(N\) represents the set of stations, \(i,j\) represent the station indices, \(i,j\in N\), and \((i,j)\) represents the set of station intervals; represents the penalty duration reference value of the interval \((i,j)\), with the unit of min; \(T\) k (i,j) represents the running duration of train \(k\) in the interval \((i,j)\), with the unit of min; represents a 0-1 variable, whose value is 1 indicating that train \(k\) stops at station \(i\) and station \(i\) meets the freight operation requirements, otherwise, its value is 0; represents a 0-1 variable, whose value is 1 indicating that train \(k\) stops at station \(j\) and station \(j\) meets the freight operation requirements, otherwise, its value is 0; In Step S42, the penalty duration calculation formula: In formula (6), Δt k,q represents the penalty duration for order q to select train k; i q represents the departure station of order q; j q represents the destination station of order q; represents the arrival time of train k at station j q ; In Step S43, the calculation method for the arrival time of the goods that meets the maximum delay time is: In formula (7), represents the arrival time of the goods that meet the maximum delay time for order q; Δh(q) represents the delay time limit for order q.

7. The method according to claim 6, characterized in that, The calculation method for determining the train alternative set is: In formulas (9)-(10), indicates whether the waiting time for the goods of order q by train k is earlier than the departure time of the train at the departure station. If it is satisfied, take 1; if not, take 0; indicates whether the latest arrival time of the goods of order q by train k is later than the arrival time of the train at the destination station. If it is satisfied, take 1; if not, take 0; β k,q indicates whether train k meets the time limit requirement of order q. If it is satisfied, take 1; if not, take 0; indicates the departure time of train k at station i q ; M represents a number much larger than other parameters.

8. The method according to claim 7, wherein The objective function in Step S7 is: In formula (11), x k,q indicates whether the goods of order q are transported by train with train number k. If selected, it takes 1; if not selected, it takes 0; c f represents the time penalty coefficient of unit containerized unit goods, with the unit of yuan / container unit·min; c k represents the unit distance cost of the corresponding train transporting unit containerized unit goods, with the unit of yuan / container unit·km; l(i q ,j q ) represents the distance of section (i q ,j q ), with the unit of km; n q represents the quantity of goods corresponding to order q.

9. The method according to claim 8, wherein In Step S8, the Gurobi solver is used to solve the train number matching optimization model.

10. A high-speed rail emergency delivery train number matching optimization system based on time limit guarantee, characterized in that, The system includes: a business division module, a front-end and back-end service time calculation module, a goods waiting time calculation module, a latest goods time determination module, a train alternative set construction module, a train number matching optimization model construction module, and a matching result output module; among them, The business division module is used to set the business process of high-speed rail express delivery, including customer shipment, pick-up and loading onto the station, inter-station transportation, and delivery and pick-up. Pick-up and loading onto the station is the front end of inter-station transportation, and delivery and pick-up is the back end of inter-station transportation; The front-end and back-end service time calculation module is used to construct the pick-up and delivery service time distribution for the two links of pick-up and loading onto the station and delivery and pick-up according to the order data and rider data; The goods waiting time calculation module is used to determine the goods waiting time according to the pick-up and delivery service time distribution, station operation time, customer appointment time, and the latest time to be delivered to the customer on the same day; The latest goods time determination module is used to determine the latest arrival time at the station for same-day delivery according to the pick-up and delivery service time distribution, station operation time, customer appointment time, and the latest time to be delivered to the customer on the same day; it is also used to obtain the penalty duration of the goods and the arrival time of the goods meeting the maximum delay time according to the train timetable, goods waiting time, delay limit, and order data; and it is used to take the smaller value between the latest arrival time at the station for same-day delivery and the arrival time of the goods meeting the maximum delay time as the latest arrival time of the goods; The train alternative set construction module is used to determine the train alternative set of the goods according to the goods time limit requirements and the OD stations of the goods; the time limit requirements include that the waiting time of the goods should be earlier than the departure time of the train at the departure station, and at the same time, the latest arrival time of the goods should be later than the arrival time of the train at the destination station; The train number matching optimization model construction module is used to construct a high-speed rail express train number matching optimization model based on timeliness guarantee and train operation cost; the constraint conditions of the objective function in the optimization model include train stop constraints, train loading capacity constraints, total goods quantity constraints, and train alternative set constraints; The matching result output module is used to solve the high-speed rail express train number matching optimization model based on timeliness guarantee, and obtain and output the train number matching result of the optimized high-speed rail express order.

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