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        1 - Bi-Objective Hybrid Flow Shop Scheduling With Pareto Approximation in a Specified Region
        Seyed Mostafa Mousavi
        This paper studies the production scheduling problem in a hybrid flow shop environment with sequence-dependent setup times and the objectives of minimizing both the maximum completion time and the total tardiness. In the past, bi-objective problems were solved by findin More
        This paper studies the production scheduling problem in a hybrid flow shop environment with sequence-dependent setup times and the objectives of minimizing both the maximum completion time and the total tardiness. In the past, bi-objective problems were solved by finding Pareto approximation in the entire problem space (without any restrictions). The limitation in this study is to find Pareto approximation in a specified region. In order to solve the problem, multi-objective genetic algorithm based on Pareto ranking has been used. In the structure of the algorithm, two strategies have been proposed in order to select solutions for archiving and produce Pareto in a certain region. After generating sample problems, the genetic algorithm has been implemented with three strategies (two proposed and one general strategy in literature). The appropriate strategy is based on efficient solutions in the archives. The results reflect the fact that the proposed strategies have shown better performance than the literature strategy. Manuscript profile