A Hybrid Nested Partitions Algorithm Combing with Genetic Algorithm for Job Shop Flexible Resource Scheduling

Abstract:

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In this paper, we formulate the Job Shop Flexible Resource Scheduling (JSFRS) problem, and presents a hybrid nested partitions algorithm combining genetic algorithm in sampling scheme for the JSFRS problem. The major part of this work is a generic partitioning scheme was implemented and the Resource Allocation Procedure was incorporated into the NP method framework. Simulation results support our theoretical results and illustrate that the hybrid nested partitions algorithm work as designed and the performance improvements associated with flexible resource scheduling are substantial.

Info:

Periodical:

Advanced Materials Research (Volumes 179-180)

Edited by:

Garry Zhu

Pages:

920-924

DOI:

10.4028/www.scientific.net/AMR.179-180.920

Citation:

W. N. Ding et al., "A Hybrid Nested Partitions Algorithm Combing with Genetic Algorithm for Job Shop Flexible Resource Scheduling", Advanced Materials Research, Vols. 179-180, pp. 920-924, 2011

Online since:

January 2011

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Price:

$35.00

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