Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Maximum-minimum ant colony optimization method and maximum-minimum ant colony optimization system for solving vehicle scheduling problem

A vehicle scheduling and optimization method technology, applied in the research field of vehicle scheduling, can solve problems such as algorithm search stagnation, and achieve the effects of good stability, strong global optimization ability, and good optimization performance.

Active Publication Date: 2015-06-10
WM MOTOR TECH GRP CO LTD
View PDF4 Cites 51 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When the algorithm iterates to a certain number of algebras, the pheromone gap on each path reaches a certain level, at this time, the algorithm will appear to a certain degree of search stagnation

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Maximum-minimum ant colony optimization method and maximum-minimum ant colony optimization system for solving vehicle scheduling problem
  • Maximum-minimum ant colony optimization method and maximum-minimum ant colony optimization system for solving vehicle scheduling problem
  • Maximum-minimum ant colony optimization method and maximum-minimum ant colony optimization system for solving vehicle scheduling problem

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0056] refer to figure 1 , a maximum-minimum ant colony algorithm for a vehicle scheduling problem without a time window includes the following steps:

[0057] Step 1: Determine cost-related cost information: fixed cost c for starting the vehicle, storage cost u for each customer point within the planning period, and fixed cost C for delivery from the distribution center to the customer point f , the unit transportation cost t from the distribution center to the customer point df , The fixed cost C of the delivery operation of the distribution center d , the loading capacity w of each distribution vehicle, and the unit transportation cost t between each customer point ij , the maximum number of iterations K_max of the outer layer of the iterative algorithm;

[0058] Step 2: Get delivery information from the order form. This information includes: customer name, total weight of goods required by the customer D i , the unloading address, the required arrival time, and the es...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a maximum-minimum ant colony optimization method and a maximum-minimum ant colony optimization system for solving a vehicle scheduling problem. The maximum-minimum ant colony optimization method comprises the following steps of acquiring address information of a customer according to delivery information in an order ticket; reading relevant information in a maximum-minimum ant colony algorithm; and performing initialization, condition termination judgment, path establishment, path improvement and information updating on the ant colony algorithm. The numerical value of pheromone polatility is changed dynamically, convergence is accelerated, a plurality of paths are searched, global searching capability of the algorithm is improved, and premature and stagnation are avoided. The maximum-minimum ant colony optimization method has the advantages that the method is easy to implement and the rapid convergence capability and the rapid searching capability are high when the method is used for solving a vehicle path problem.

Description

technical field [0001] The invention relates to the research field of vehicle scheduling, in particular to an improved maximum-minimum ant colony optimization method and system for vehicle scheduling problems. Background technique [0002] Vehicle routing problem (Vehicle Routing Problem, VRP) can generally be described as: n customers are scattered in a certain area, each has a different quantity of goods demand, a distribution center provides goods to customers, and m vehicles are responsible for distributing goods, The goal of organizing appropriate driving routes is to satisfy the needs of customers, and achieve the goals such as the shortest distance, the smallest cost, and the least time-consuming under certain constraints. The simplest and most classic VRP problem requires that the travel route of each vehicle minimize the total transportation cost, and ensure that each service demand point is visited only once by one of the vehicles. [0003] VRP, also known as the ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/08G06Q50/28G06N3/00
Inventor 谢骊玲宋彦斌骆其伦
Owner WM MOTOR TECH GRP CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Eureka Blog
Learn More
PatSnap group products