An efficient tabu search approach for the two-machine preemptive open shop scheduling problem
Computers and Operations Research
Computers and Operations Research
A new particle swarm optimization for the open shop scheduling problem
Computers and Operations Research
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Approximation algorithms for the multiprocessor open shop scheduling problem
Operations Research Letters
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This paper considers an open shop scheduling problem that minimizes bi-objectives, namely makespan and total tardiness. This problem, due to its complexity, is ranked in the class of NP-hard problems. In this case, traditional approaches cannot reach to an optimal solution in a reasonable time. Thus, we propose an efficient method based on multi-objective simulated annealing and ant colony optimization, in order to solve the given problem. Furthermore a decoding operator is applied in order to improve the quality of generated schedules. Finally, we compare our computational results with a well-known multi-objective genetic algorithm, namely NSGA II. In addition, comparisons are made in single objective case. The outputs show encouraging results in the form of the solution quality.