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Self-adapted Hybrid Genetic Algorithm for Job Scheduling of Distributed Manufacturing System

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3 Author(s)
Jingsong Yang ; Coll. of Comput. Sci. & Technol., Changchun Univ. of Sci. & Technol., Changchun ; Guangcai Cui ; Xuedan Hu

An approach using the concept of self-adapted hybrid genetic algorithm (AGASA) is proposed as a powerful but simple means to optimize job scheduling in distributed manufacturing system (DMS). A directed graph model is developed to describe the characteristics of DMS. The superiority of the proposed algorithm is illustrated by computing result with pattern of GANTT graph, and the results are compared with methods of genetic algorithm and simulated annealing algorithm.

Published in:

Bio-Inspired Computing: Theories and Applications, 2007. BIC-TA 2007. Second International Conference on

Date of Conference:

14-17 Sept. 2007