Improved artificial fish school optimization method based on vehicle path planning

An artificial fish school and vehicle path technology, applied in the engineering field, can solve the problems of low precision of optimization results, slow operation speed, and poor ability of the algorithm to maintain a balance between exploration and development, and achieve the effect of improving the global search ability.

Inactive Publication Date: 2010-10-20
HANGZHOU DIANZI UNIV
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Problems solved by technology

However, the algorithm is poor in maintaining the balance between exploration and development, the blindness of the search in the later stage of the algorithm is relatively large, the precision of the optimization result is low, and the operation speed is slow, etc.

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  • Improved artificial fish school optimization method based on vehicle path planning
  • Improved artificial fish school optimization method based on vehicle path planning
  • Improved artificial fish school optimization method based on vehicle path planning

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Embodiment Construction

[0029] An improved artificial fish swarm optimization method based on vehicle path planning, specifically comprising the following steps:

[0030] Step 1. Considering the characteristics of the VRPB problem, randomly generate artificial fish schools of initial size. The state of the vehicle in period t is defined by the state vector X=(X i(t), i=1, 2, ..., F_number) represents, wherein, i is the node that the vehicle will serve, X i (t) is the loadable capacity of the current vehicle; the objective function Y i =F(X i (t)) determines the food concentration at the current location of the artificial fish; the distance between individual artificial fish is expressed as d i，i+1 =‖X i -X i+1 ‖; For the VRPB problem, the initial position of the artificial fish needs to be placed on the starting point and the ending point, because the vehicle is only valid if it starts from the starting point and reaches the end point, or returns to the starting point from the end point.

[003...

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Abstract

The invention relates to an improved artificial fish school optimization method based on vehicle path planning. The existing algorithm has the defects of large calculation amount and long time consumption. The invention effectively combines the bionics principle of the artificial fish school and the subjective bias of a decision maker, improves the artificial fish school algorithm, and introduces the concept of a fish school sensing range for reconstructing an optimization formula of the artificial fish school algorithm by a repulsion region, a neutral region and an attracting region. The moving step length of the artificial fish, the view field range and the adjacent field value are dynamically regulated through judging the demands of nodes on the vehicle path, the reset transportation capability of the current vehicles, and the subjective bias of the decision maker, so the overall searching capability and the searching speed of the artificial fish school algorithm can be improved. Finally, the improved artificial fish school algorithm is used for improving the cargo taking and cargo sending behaviors of the vehicles and completing the path dispatching problem of return trip cargo taking vehicles. The invention is superior to the traditional optimization algorithms such as the genetic algorithm, the simulation annealing algorithm and the like in aspects of calculation precision and stability, and has good optimization capability.

Description

technical field [0001] The invention belongs to the technical field of engineering and relates to an improved artificial fish swarm optimization method based on vehicle path planning. Background technique [0002] In recent years, my country has vigorously advocated a circular economy that "adhere to equal emphasis on development and conservation, give priority to conservation, and follow the principles of reduction and reuse of resources". Most manufacturing companies have implemented the extended producer responsibility system and remanufactured recalled waste products . A typical example is the "customer self-replacement of spare parts unit" adopted by the spare parts logistics department of Lenovo Group. The process is that the company delivers new computer accessories to end customers and provides door-to-door service, and at the same time retrieves damaged computer accessories. This two-way transportation method is a typical Vehicle Routing Problem with Backhaul (VRPB)...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/00
Inventor 柳毅王晓耘魏洁
Owner HANGZHOU DIANZI UNIV
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