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A genetic algorithm for scheduling of jobs on lines of press machines

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Akademik Birimler

Kurum Yazarları

Özalp, Selma Ayşe

Yazarlar

Lirkov, I.
Margenov, S.
Wasniewski, J.

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Springer

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Özet

This paper introduces a Genetic Algorithm (GA) based solution technique for press machines scheduling problem of a car manufacturing factory. Firstly, the problem at hand, and the application of the CA in terms of coding, chromosome evaluation, crossover and Mutation operators, are described in detail. After that, the CA is experimentally evaluated through some test problems. As the objective of the problem is the minimization of the completion time of the jobs, the CA based solution is compared with the Longest Processing Time (LPT) rule, and it is observed that the CA always produces better schedules than the LPT rule in a reasonably short amount of CPU time.

Açıklama

Bu çalışma, 06-10, Haziran 2005 tarihlerinde Sozopol[Bulgaristan]’da düzenlenen 5. International Conference on Large-Scale Scientific Computing (LSSC 2005) Kongresi‘nde bildiri olarak sunulmuştur.

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Konusu

Computer science, Parallel machines, Scheduling, Program processors, Problem solving, Mutagens, Chromosomes, Press machines, Longest processing time (LPT) rule, Chromosome evaluation, Genetic algorithms

Alıntı

Özalp, S. A. (2006). ''A genetic algorithm for scheduling of jobs on lines of press machines''. ed. İ. Lirkov, S. Margenov, J. Wasniewski. Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 3743, 535-543.

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