Whole vehicle logistics scheduling optimization method based on improved genetic algorithm
The invention discloses a whole vehicle logistics scheduling optimization method based on an improved genetic algorithm. The method comprises the steps of obtaining order information, transport vehicle information, commercial vehicle information and parking lot information; determining a function op...
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creator | ZHANG LIJIE XIONG JUNXING SHAO CHAOFEI LIU JIANSHENG YUAN BIN YANG ZAN |
description | The invention discloses a whole vehicle logistics scheduling optimization method based on an improved genetic algorithm. The method comprises the steps of obtaining order information, transport vehicle information, commercial vehicle information and parking lot information; determining a function optimization target and constraint conditions; setting a population size, a crossover probability, a mutation probability and an iteration termination condition; performing population initialization and gene coding: adopting double-chromosome natural number coding, namely order chromosome coding and transport vehicle chromosome coding; dynamically decoding the code and calculating a function fitness value; and repeating the following operations: selection operation, crossover operation, mutation operation and local optimization operation until a termination condition is reached, and outputting an optimal scheme. Through the improved genetic algorithm, greedy algorithm initial population optimization, double chromosom |
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The method comprises the steps of obtaining order information, transport vehicle information, commercial vehicle information and parking lot information; determining a function optimization target and constraint conditions; setting a population size, a crossover probability, a mutation probability and an iteration termination condition; performing population initialization and gene coding: adopting double-chromosome natural number coding, namely order chromosome coding and transport vehicle chromosome coding; dynamically decoding the code and calculating a function fitness value; and repeating the following operations: selection operation, crossover operation, mutation operation and local optimization operation until a termination condition is reached, and outputting an optimal scheme. 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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
title | Whole vehicle logistics scheduling optimization method based on improved genetic algorithm |
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