Abstract
Exact and heuristic algorithms have been proposed over the years for solving static permutation flow shop scheduling problems with the objectives of minimising makespan, total tardiness, and total flow time, etc. Of late, attempts are being made to consider more than one objective at a time, and develop algorithms in order to obtain a set of Pareto-optimal solutions. In such multi-objective scheduling problems, it is common to obtain a set of Pareto-optimal or efficient solutions such that at least one such solution is not inferior to any other given solution not contained in the set, and the solutions in that set does not dominate each other. In this paper, we consider a multi-objective permutation flow shop problem with the aim of generating non-dominated solutions with the aim of minimising makespan and maximum tardiness of jobs. A multi-objective simulated annealing (MOSA) algorithm has been developed towards this purpose. The proposed algorithm is evaluated using randomly generated problems. The effi...
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