CN106803136A - A kind of fresh dispatching real-time optimization method based on genetic algorithm - Google Patents

A kind of fresh dispatching real-time optimization method based on genetic algorithm Download PDF

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CN106803136A
CN106803136A CN201710053599.9A CN201710053599A CN106803136A CN 106803136 A CN106803136 A CN 106803136A CN 201710053599 A CN201710053599 A CN 201710053599A CN 106803136 A CN106803136 A CN 106803136A
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欧阳芳
姚晓东
薛均
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Suzhou Vocational Institute of Industrial Technology
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Abstract

The invention discloses a kind of fresh dispatching real-time optimization method based on genetic algorithm, it is characterized in that, using Floyd (City Routine delivery point) algorithm, Dijkstra (city dynamic delivery point) algorithm, calculate the shortest path between delivery point, and Distribution path is merged using mileage method is saved, then the Distribution path of each delivery point is carried out with genetic algorithm integrated.The beneficial effect that the present invention is reached：This method, by genetic algorithm, with reference to distribution cost is optimized, can realize that real-time routes are distributed in dispatching in real time, for the appearance of various dynamic delivery points, improve overall allocative efficiency, have great meaning for fresh dispatching.

Description

A kind of fresh dispatching real-time optimization method based on genetic algorithm
Technical field
The present invention relates to a kind of fresh dispatching real-time optimization method based on genetic algorithm, belong to logistics distribution algorithm Technical field.
Background technology
The fresh dispatching business of current city rapidly rises, and multi items, small batch, dispatching point skewness, friendship is presented Situations such as logical congestion is frequent.Meanwhile, client is frequently changed to sequence information immediately by mobile electric business platform, also significantly Improve the difficulty of fresh delivery operation plan.
On the one hand fresh dispatching efficiency influence fresh product quality, on the other hand associates the economic well-being of workers and staff of distribution enterprise.It is long Since phase, the fresh dispatching in city faces that profit is low, timeliness is high, the high request complex job of multi items, small batch always.Also, Different with common Distribution path planning, fresh dispatching in face of numerous city dwellers due to consuming, and the dynamic variable of dispatching is more, Dispense desired timeliness higher.
In the operation management of actual home-delivery center, path, the plan of fresh dispatching are often by deliveryman according to specific feelings Condition independently determines, lacks a systematicness, scientific cost accounting and optimization design.
The content of the invention
It is to solve the deficiencies in the prior art, matches somebody with somebody it is an object of the invention to provide a kind of fresh based on genetic algorithm Real-time optimization method is sent, efficiency is low when can solve the problem that implementation dispatching at present is fresh, the problem of high cost.
In order to realize above-mentioned target, the present invention is adopted the following technical scheme that：
A kind of fresh dispatching real-time optimization method based on genetic algorithm, it is characterized in that, comprise the following steps：
1) according to home-delivery center and the position of each delivery point, using Floyd algorithms and dijkstra's algorithm, with reference to storehouse Storage expense, transhipment charge and administration fee, are solved with always dispensing the minimum optimization aim of expense, are calculated between delivery point Shortest path；
2) using saving mileage method to step 1) each shortest path for obtaining merges；
3) according to resource the combination step 2 of current dispatching website) result carry out path division, calculate it is static under dispatching The minimum cost object function of route, forms some distribution routes；
4) delivery information is monitored in real time, if changed to delivery information, using genetic algorithm again Construction distribution route；Specifically reconfigure step as follows：
Step 401) coding method that directly arrange using delivery point, representing all with a matrix needs what completions were dispensed The order of delivery point, the numbering of delivery point is made up of 1~n；
The delivery point that will be accessed is randomly formed sequence, and each delivery point is added into current dispatching one by one in order In route；Check whether to meet vehicle load limitation, if meeting, the delivery point is added in current distribution route；If no Meet, then add it to next distribution route；
Step 402) calculating+cost objective function, G is the infeasible path bar number of individual corresponding Distribution path scheme：
If current distribution route number<The total number of units of vehicle, then G=0, represents the individuality one feasible solution of correspondence；
If current distribution route number >=total number of units of vehicle, G>0, represent the individuality without solution；
PwRepresent to every punishment weight of infeasible path, fitness value meets Optimality Criteria；
Step 403) selection new individual delivery point；Individual delivery with upper zone degree of appearance is selected using random algorithm Point；Using current delivery point set as filial generation, retain the optimal solution of current delivery point set, and keep the delivery colony of filial generation Number is identical with total group number of individuals；
Step 404) crossover operation repeatedly is carried out as cross method using the improved OX methods of class.
Further, the step 1) in by Floyd algorithms obtain between delivery point shortest path distance, need transfer Number of times and distribution time；Fresh goods delivery amount and transfer amount are calculated by dijkstra's algorithm, and according to freight rate, dispatching Amount and distance obtain cost of transportation.
Further, the step 2) concretely comprise the following steps：
21) home-delivery center to the beeline between delivery point, delivery point is measured；
22) corresponding saving mileage number is tried to achieve by saving mileage formula；
23) according to vehicle load as constraints and the size for saving mileage number, be linked in sequence each delivery point node；
24) each shortest path that will be obtained is merged.
Further, the step 3) in dispatching website resource include vehicle-mounted heavy, vehicle volume, plan arrange car Number X, average speed V, unit dispatching rate be c, the daily maximum operating range of vehicle be L, after maximum operating range The rejection penalty that it is pl to the expense of driver that every kilometer needs additional pay, time-to-violation window is constrained is the early expense p for arriving1Arrived with evening Expense p2。
Further, the step 3) in minimum cost object function：
Extra cost after range
The punishment cost of time-to-violation window limitation
The above-mentioned basic constraints that is related to is：These three are about in condition One is to ensure each customer only no more than its maximum carrying capacity ability, following two constraints to ensure each distribution vehicle Can be assigned on a paths, i.e., each customer dispatching number of times is 1 time；
Wherein, N represents dispatching point and the set of this actual delivery point code name, and dispatching point is labeled as 0；M represents actual peace The vehicle set of row, c0Represent and send a fixed cost for car, dijThe distance between any two delivery point is represented, Q represents every The maximum dispensed amounts of car, LkThe distance that expression has been travelled, p0It is the starting expense of vehicle, xijkRepresent vehicle k by path (i, J), value is 1, and the delivery amount of delivery point i is qi, the delivery time requirement of delivery point i is in time window [ETi,LTi] in, TAiFor It is actually reached the time of delivery point i, [ai,bi] represent the time range that the time of delivery (TOD) of delivery point i requirement goods must not exceed, A Represent and exceed [ai,bi] delivery time scope punishment cost value, empirically value setting.
Further, the step 402) in Optimality Criteria be specially：Optimum results such as converge to permissible accuracy scope, Using the convergence precision of optimization as Optimality Criteria, otherwise according to the maximum emulation algebraically of dijkstra's algorithm as termination condition.
The beneficial effect that the present invention is reached：This method can be in dispatching in real time, for going out for various dynamic delivery points It is existing, by genetic algorithm, with reference to distribution cost is optimized, realize that real-time routes are distributed, overall allocative efficiency is improved, it is right There is great meaning in fresh dispatching.
Specific embodiment
The invention will be further described below.Following examples are only used for clearly illustrating technical side of the invention Case, and can not be limited the scope of the invention with this.
In the present embodiment by taking the fresh Distribution path planning of the Suzhou fresh enterprise of food row as an example：
Known fresh home-delivery center's coordinate is (137,93), and vehicle load is 5 tons, vehicle volume is 354 × 795 × 220cm, vehicle can accommodate 20 standard turnover boxes (i.e. standard dispatching unit), and the delivery amount of all delivery point demands is respectively less than matches somebody with somebody Send the maximum load ability of vehicle, vehicle by home-delivery center Suzhou across the pool, must return to across pool dispatching after completing dispatching task Center.
Dispatching rate c=1 units/kilometer, send a fixed cost c for car more0=100 yuan, the dispatching of vehicle maximum cargo 5 tons of amount, most 300 kilometers of the daily operating range of vehicle needs additional pay to give yuan/kilometer of driver 1.2 beyond 300 kilometers every kilometer Expense, it is assumed that 50 kilometers of average speed/when, with the 1/3 of delivery amount (ton) for the delivery point service time (hour).
Assuming that starting point has 8 dispatching tasks of delivery point, shown in the delivery amount following table of each delivery point requirement：
Delivery point 1 4 5 8 15 16 17 22
Delivery amount (ton) 2 1.5 2.5 5 1.5 2.5 3 2.5
Time window [0,2] [0.5,3] [2,4] [Isosorbide-5-Nitrae] [3,7] [2,5] [0.5,2] [2,5]
Position coordinates (kilometer) (95,55) (134,50) (160,48) (175,90) (58,92) (71,73) (84,76) (184,71)
Table 1
Assuming that after new delivery point occurs in the T moment (instantaneity), waiting in line shown in the situation such as following table (table 2) of delivery：
Table 2
Computing is carried out according to above-mentioned data, if distribution route is not changed, delivery route and cost such as following table (table 3)：
Table 3 is based on the cost accounting of static distribution route
If carrying out the adjustment of distribution route using method involved in the present invention, the distribution project such as following table can be obtained：
Table 4 is based on the distribution route cost accounting of dynamic adjustment
Data above is explicitly shown, and is generated new matching somebody with somebody by the genetic algorithm of the mixed type for being used in the present invention Sending path can save 22.4% dispatching expense.
Be can see from the explanation of above example, this method can improve the speed of fresh dispatching, it is ensured that fresh Quality, while reducing enterprise's distribution cost, quick response customer demand, and can improve vehicle utilization rate, and low-carbon energy-saving subtracts Few urban traffic blocking, finally by Circulation of Agricultural Products efficiency, promotes the healthy and rapid development of agricultural industry chain.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art For member, on the premise of the technology of the present invention principle is not departed from, some improvement and deformation can also be made, these improve and deform Also should be regarded as protection scope of the present invention.

Claims (6)

1. a kind of fresh dispatching real-time optimization method based on genetic algorithm, it is characterized in that, comprise the following steps：
1) according to home-delivery center and the position of each delivery point, using Floyd algorithms and dijkstra's algorithm, with reference to warehousing charge With, transhipment charge and administration fee, solved with always dispensing the minimum optimization aim of expense, calculated between delivery point most Short path；
2) using saving mileage method to step 1) each shortest path for obtaining merges；
3) according to resource the combination step 2 of current dispatching website) result carry out path division, calculate it is static under distribution route Minimum cost object function, formed some distribution routes；
4) delivery information is monitored in real time, if changed to delivery information, is reconfigured using genetic algorithm Distribution route；Specifically reconfigure step as follows：
Step 401) coding method that directly arrange using delivery point, represent all delivery for needing completions to dispense with a matrix The order of point, the numbering of delivery point is made up of 1~n；
The delivery point that will be accessed is randomly formed sequence, and each delivery point is added into current distribution route one by one in order In；Check whether to meet vehicle load limitation, if meeting, the delivery point is added in current distribution route；If it is not satisfied, Then add it to next distribution route；
Step 402) calculating+cost objective function, G is the infeasible path bar number of individual corresponding Distribution path scheme：
If current distribution route number<The total number of units of vehicle, then G=0, represents the individuality one feasible solution of correspondence；
If current distribution route number >=total number of units of vehicle, G>0, represent the individuality without solution；
PwRepresent to every punishment weight of infeasible path, fitness value meets Optimality Criteria；
Step 403) selection new individual delivery point；Individual delivery point with upper zone degree of appearance is selected using random algorithm； Using current delivery point set as filial generation, retain the optimal solution of current delivery point set, and keep the delivery colony number of filial generation It is identical with total group number of individuals；
Step 404) crossover operation repeatedly is carried out as cross method using the improved O X methods of class.
2. a kind of fresh dispatching real-time optimization method based on genetic algorithm according to claim 1, it is characterized in that, The step 1) in shortest path distance between delivery point obtained by Floyd algorithms, need the number of times and distribution time of transfer； Fresh goods delivery amount and transfer amount are calculated by dijkstra's algorithm, and transport is obtained according to freight rate, dispensed amounts and distance Cost.
3. a kind of fresh dispatching real-time optimization method based on genetic algorithm according to claim 1, it is characterized in that, The step 2) concretely comprise the following steps：
21) home-delivery center to the beeline between delivery point, delivery point is measured；
22) corresponding saving mileage number is tried to achieve by saving mileage formula；
23) according to vehicle load as constraints and the size for saving mileage number, be linked in sequence each delivery point node；
24) each shortest path that will be obtained is merged.
4. a kind of fresh dispatching real-time optimization method based on genetic algorithm according to claim 1, it is characterized in that, The step 3) in dispatching website resource include vehicle-mounted heavy, vehicle volume, plan arrange vehicle number X, average speed V, Unit dispatching rate be c, the daily maximum operating range of vehicle be L, every kilometer after maximum operating range need additional pay The rejection penalty that expense to driver is pl, time-to-violation window is constrained is the early expense p for arriving1The expense p arrived with evening2。
5. a kind of fresh dispatching real-time optimization method based on genetic algorithm according to claim 4, it is characterized in that, The step 3) in minimum cost object function：
min Z = c &Sigma; k &Element; M &Sigma; i &Element; N &Sigma; j &Element; N d i j x i j k + c 0 &Sigma; k &Element; M &Sigma; j &Element; N x 0 j k + &Sigma; k &Element; M P L ( k ) + &Sigma; i &Element; N P T ( i ) ;
Extra cost after range
The punishment cost of time-to-violation window limitation
The above-mentioned basic constraints that is related to is：
Wherein, N represents dispatching point and the set of this actual delivery point code name, and dispatching point is labeled as 0；M represents actual arrangement Vehicle set, c0Represent and send a fixed cost for car, dijThe distance between any two delivery point is represented, Q represents each car Maximum delivery amount, p0It is the starting expense of vehicle, xijkVehicle k is represented by path (i, j), value is 1, and delivery point i's send Goods amount is qi, the delivery time requirement of delivery point i is in time window [ETi,LTi] in, TAiTo be actually reached the time of delivery point i, [ai,bi] time range that the time of delivery (TOD) of delivery point i requirement goods must not exceed is represented, A is represented beyond [ai,bi] when being sent to Between scope punishment cost value, empirically value setting.
6. a kind of fresh dispatching real-time optimization method based on genetic algorithm according to claim 3, it is characterized in that, The step 402) in Optimality Criteria be specially：Optimum results such as converge to permissible accuracy scope, with the convergence precision for optimizing As Optimality Criteria, otherwise according to the maximum emulation algebraically of dijkstra's algorithm as termination condition.
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CN107358326A (en) * 2017-07-20 2017-11-17 深圳市凯立德科技股份有限公司 A kind of bicycle multiple spot dispenses circuitry processing method
CN107607123A (en) * 2017-08-25 2018-01-19 骆剑锋 The path planning algorithm of the multi-destination of consideration limit for tonnage limit distance based on more vehicles
CN107644270A (en) * 2017-09-19 2018-01-30 广州唯品会研究院有限公司 Paths planning method, device and the computer-readable recording medium of unmanned dispatching
CN107977739A (en) * 2017-11-22 2018-05-01 深圳北斗应用技术研究院有限公司 Optimization method, device and the equipment in logistics distribution path
CN108133342A (en) * 2017-12-21 2018-06-08 家乐宝电子商务有限公司 A kind of Logistics Distribution Method, device, equipment and computer readable storage medium
CN108446923A (en) * 2018-01-31 2018-08-24 安庆师范大学 A kind of task pricing method based on self-service labor service crowdsourcing platform
CN108830403A (en) * 2018-05-23 2018-11-16 广西中烟工业有限责任公司 The tobacco retail customer calculated based on commercial value visits path visual analysis method
CN108932563A (en) * 2018-07-03 2018-12-04 江苏海事职业技术学院 One kind interconnects formula harbour information platform Intelligent Dispatching System
CN108985677A (en) * 2018-06-11 2018-12-11 华东理工大学 The multiple batches of fresh agricultural products Distribution path optimization method of multi items
CN109214608A (en) * 2018-11-14 2019-01-15 成都英孚克斯科技有限公司 A kind of vehicle scheduling optimization method
CN109345161A (en) * 2018-08-29 2019-02-15 广西大学 A kind of delivery assignment method towards monetary value flow
CN109801014A (en) * 2018-12-28 2019-05-24 国网天津市电力公司电力科学研究院 Electric energy metering device dispatching scheduling method and program system based on genetic algorithm
CN111080214A (en) * 2020-01-02 2020-04-28 汉口北进出口服务有限公司 Logistics distribution path determining method and device and storage medium
CN112200367A (en) * 2020-10-09 2021-01-08 河北工业大学 Electric vehicle distribution path optimization method supporting charge-discharge strategy
CN110046749B (en) * 2019-03-22 2021-05-11 杭州师范大学 E-commerce package and co-city o2o package co-distribution system based on real-time road conditions
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CN107607123B (en) * 2017-08-25 2019-04-16 骆剑锋 Based on the considerations of the paths planning method of the multi-destination of more vehicle limits for tonnage limit distance
CN107607123A (en) * 2017-08-25 2018-01-19 骆剑锋 The path planning algorithm of the multi-destination of consideration limit for tonnage limit distance based on more vehicles
CN107644270A (en) * 2017-09-19 2018-01-30 广州唯品会研究院有限公司 Paths planning method, device and the computer-readable recording medium of unmanned dispatching
CN107644270B (en) * 2017-09-19 2021-06-25 广州唯品会研究院有限公司 Unmanned distribution path planning method, device and computer readable storage medium
CN107977739A (en) * 2017-11-22 2018-05-01 深圳北斗应用技术研究院有限公司 Optimization method, device and the equipment in logistics distribution path
CN107977739B (en) * 2017-11-22 2021-07-06 深圳北斗应用技术研究院有限公司 Method, device and equipment for optimizing logistics distribution path
CN108133342A (en) * 2017-12-21 2018-06-08 家乐宝电子商务有限公司 A kind of Logistics Distribution Method, device, equipment and computer readable storage medium
CN108446923A (en) * 2018-01-31 2018-08-24 安庆师范大学 A kind of task pricing method based on self-service labor service crowdsourcing platform
CN108830403A (en) * 2018-05-23 2018-11-16 广西中烟工业有限责任公司 The tobacco retail customer calculated based on commercial value visits path visual analysis method
CN108830403B (en) * 2018-05-23 2022-03-22 广西中烟工业有限责任公司 Visual analysis method for tobacco retail customer visiting path based on commercial value calculation
CN108985677B (en) * 2018-06-11 2022-07-08 华东理工大学 Method for optimizing distribution path of multiple varieties of fresh agricultural products in multiple batches
CN108985677A (en) * 2018-06-11 2018-12-11 华东理工大学 The multiple batches of fresh agricultural products Distribution path optimization method of multi items
CN108932563A (en) * 2018-07-03 2018-12-04 江苏海事职业技术学院 One kind interconnects formula harbour information platform Intelligent Dispatching System
CN109345161B (en) * 2018-08-29 2022-02-25 广西大学 Value flow-oriented distribution order dispatching method
CN109345161A (en) * 2018-08-29 2019-02-15 广西大学 A kind of delivery assignment method towards monetary value flow
CN109214608A (en) * 2018-11-14 2019-01-15 成都英孚克斯科技有限公司 A kind of vehicle scheduling optimization method
CN109214608B (en) * 2018-11-14 2022-01-25 成都英孚克斯科技有限公司 Vehicle scheduling optimization method
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Application publication date: 20170606