Golden annealing method for job shop scheduling problem

Authors:
Juan Frausto-Solis;Felix Martinez-Rios
Affiliations:
ITESM, Department of Computer Science, Morelos, Mexico;Universidad Panamericana, Engineering School, Mexico
Venue:
MACMESE'08 Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering
Year:
2008

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Abstract

The representation of Job Shop Scheduling Problem (JSSP) as the well known Satisfiabilty Problem (SAT) is useful to find feasible schedules in an efficient way. One of the most efficient SAT codifications of JSSP is RSF (Reduced Sat Codification) which transforms any JSSP instance to a 3-SAT problem. In this paper a new method called GASAT (Golden Annealing with SAT codification) is presented. Starting with a random JSSP solution, GASAT finds its 1-SAT representation and evaluates whether it is feasible or not. Experimentation presented in the paper shows that both, the new codification and algorithm are more efficient than the ones previously reported.