Accessing feasible space in a generalized job shop scheduling problem with the fuzzy processing times: a fuzzy-neural approach

R Tavakkoli-Moghaddam (), N Safaei and M M O Kah
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R Tavakkoli-Moghaddam: University of Tehran
N Safaei: Iran University of Science and Technology
M M O Kah: Abti-American University of Nigeria, Yola, Nigeria and American University

Journal of the Operational Research Society, 2008, vol. 59, issue 4, 431-442

Abstract: Abstract This paper presents a fuzzy-neural approach for constraint satisfaction of a generalized job shop scheduling problem (GJSSP) fuzzy processing times. Our study is an extension of recently developed research in a GJSSP where the processing time of operations was constant. Our paper assumes that the processing time of jobs is uncertain. The proposed fuzzy-neural approach can be adaptively adjusted with weights of connections based on sequence resource and uncertain processing time constraints of the GJSSP during its processing. The computational results show that the proposed neural approach is able to find good solutions in reasonable time.

Keywords: generalized job shop scheduling; fuzzy processing time; constraint satisfaction; neural networks (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (3)

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DOI: 10.1057/palgrave.jors.2602351

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