A total tardiness transport plan scheduling algorithm based on improved particle swarm optimization

The invention provides a total tardiness transport plan scheduling algorithm based on improved particle swarm optimization. The algorithm comprises the steps of firstly, establishing a total tardiness value mathematic model based on input variables and defining the number n of to-be-processed works...

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Hauptverfasser: YI YANG, LI FANG, TU GUANPING, CHEN XINGENG, WU SIYANG, ZHAO YONGXIAN
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creator YI YANG
LI FANG
TU GUANPING
CHEN XINGENG
WU SIYANG
ZHAO YONGXIAN
description The invention provides a total tardiness transport plan scheduling algorithm based on improved particle swarm optimization. The algorithm comprises the steps of firstly, establishing a total tardiness value mathematic model based on input variables and defining the number n of to-be-processed works and the number m of machines, and the time pj required for processing of each to-be-processed work and the delivery term dj; secondly, solving a construction drawing according to the total tardiness value mathematic model; thirdly, based on the construction drawing and according to state transition rules and pheromone update rules, completing search and acquiring a solution making the total tardiness T minimum. Based on the ant colony algorithm and according to the characteristics of the total tardiness transport plan scheduling problem (P//T) of parallel machines, the improved Heuristic Ant Colony Optimization (hACO) is proposed and performance optimization research is performed on the algorithm to improve the det
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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 A total tardiness transport plan scheduling algorithm based on improved particle swarm optimization
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