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A hybrid genetic algorithm for the job shop scheduling problem

José F. Gonçalves (jfgoncal***at***fe.up.pt)
Jorge José M. Mendes (jmendes***at***fe.up.pt)
Mauricio G. C. Resende (mgcr***at***research.att.com)

Abstract: This paper presents a hybrid genetic algorithm for the Job Shop Scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.

Keywords: Job Shop, Scheduling, Genetic Algorithm, Heuristics, Random Keys

Category 1: Applications -- OR and Management Sciences (Scheduling )

Category 2: Combinatorial Optimization (Meta Heuristics )

Citation: AT&T Labs Research Technical Report TD-5EAL6J, AT&T Labs Research, 180 Park Avenune, Florham Park, NJ 07932 USA, September 2002.

Download: [PDF]

Entry Submitted: 09/24/2002
Entry Accepted: 09/24/2002
Entry Last Modified: 09/24/2002

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