Digital Library of the European Council for Modelling and Simulation

Title:	Using A Bee Colony Algorithm For Neighborhood Search In Job Shop Scheduling Problems
Authors:	Chin Soon Chong, Malcolm Yoke Hean Low, Appa Iyer Sivakumar, Kheng Leng Gay
Published in:	ECMS 2007 Proceedings Edited by: Ivan Zelinka, Zuzana Oplatkova, Alessandra Orsoni ISBN: 978-0-9553018-2-7 Doi: 10.7148/2007 21^st European Conference on Modelling and Simulation, Prague, June 4-6, 2007
Citation format:	Chong, C. S., Low, M. Y. H., Sivakumar, A. I., & Gay, K. L. (2007). Using A Bee Colony Algorithm For Neighborhood Search In Job Shop Scheduling Problems. ECMS 2007 Proceedings edited by: I. Zelinka, Z. Oplatkova, A. Orsoni (pp. 459-465). European Council for Modeling and Simulation. doi:10.7148/2007-0459.
DOI:	http://dx.doi.org/10.7148/2007-0459
Abstract:	This paper describes a population-based approach that uses a honey bees foraging model to solve job shop scheduling problems. The algorithm applies an efficient neighborhood structure to search for feasible solutions and iteratively improve on prior solutions. The initial solutions are generated using a set of priority dispatching rules. Experimental results comparing the proposed honey bee colony approach with existing approaches such as ant colony, tabu search and shifting bottleneck procedure on a set of job shop problems are presented. The results indicate the performance of the proposed approach is comparable to other efficient scheduling approaches.
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