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A new encoding scheme for solving job shop problems by genetic algorithm

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3 Author(s)
Guoyong Shi ; Dept. of Electron. & Inf. Sci., Kyoto Inst. of Technol., Japan ; H. Iima ; N. Sannomiya

A new encoding scheme in genetic algorithms is proposed by using an ordering string for the classic job shop scheduling problem. A genetic algorithm is designed for searching the semi-active schedule space, which is encoded by the string space. A new crossover, set-partition crossover is introduced in accompanying the genetic searching. An associated selection strategy and a production structure are properly established for this fashion of encoding. This encoding scheme naturally overcomes the infeasibility problem in genetic iterations. Experiments show that the proposed genetic algorithm is effective, and optimal solutions are attainable in some probability for Fisher and Thompson problems with definite hardness

Published in:

Decision and Control, 1996., Proceedings of the 35th IEEE Conference on  (Volume:4 )

Date of Conference:

11-13 Dec 1996