DocumentCode
3289278
Title
Application Job-Shop Scheduling Problems Based on Improved Genetic Algorithm to Engineering Equipment´s Rush-Repair in Battlefield
Author
Zhang, Qiyi ; Wang, Wentao
Author_Institution
Automobile Manage. Inst. of PLA, Bengbu, China
fYear
2009
fDate
16-17 May 2009
Firstpage
314
Lastpage
317
Abstract
Engineering equipmentpsilas rush repairs in battlefield optimal assignment model was established. Combining the features of job shop scheduling problems, described the complexity of this problem. In order to find global optimal results efficiently, traditional GAs were improved and used for study of this problem. Though genetic algorithm, as an effective global search method, had been used in many engineering problems, it had the disadvantages of slow convergence and poor stability in practical engineering. In order to overcome these problems, an improved genetic algorithm was proposed in terms of creation of the initial population, genetic operators, etc. At the end, the steps to solve the optimal model were put forward. With this model we had obtained ideal results. This shows that the method can offer a scientific and effective support for a decision maker in command automation of the engineering equipmentpsilas rush repairs in battlefield.
Keywords
genetic algorithms; job shop scheduling; maintenance engineering; search problems; battlefield optimal assignment model; command automation; decision maker; engineering equipment; genetic algorithm; job shop scheduling; rush repairs; Automobiles; Automotive engineering; Circuits; Conference management; Electronic mail; Engineering management; Genetic algorithms; Genetic engineering; Programmable logic arrays; Search methods; engineering equipment; genetic algorithm; job-shop scheduling; rush-repairs in battlefield;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits, Communications and Systems, 2009. PACCS '09. Pacific-Asia Conference on
Conference_Location
Chengdu
Print_ISBN
978-0-7695-3614-9
Type
conf
DOI
10.1109/PACCS.2009.118
Filename
5232349
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