An Efficient Genetic Algorithm for Two-stage Hybrid Flow Shop Scheduling with Preemption and Sequence Dependent Setup Time


Authors

Hany Seidgar - Department of industrial engineering, Mazandaran University of science and technology, Iran. Mehrdad Ezzati - Department of industrial engineering, Mazandaran University of science and technology, Iran. Morteza Kiani - Department of industrial engineering, Mazandaran University of science and technology, Iran. Reza Tavakkoli-moghaddam - Department of industrial engineering College of Engineering, University of Tehran, Iran.


Abstract

In This paper a two stages Hybrid Flow Shop (HFS) problem with sequence dependent set up times is considered in which the preemption is also allowed. The objective is to minimize the weighted sum of completion time and maximum tardiness. Since this problem is categorized as an NP-hard one, meta-heuristic algorithms can be utilized to obtain high quality solutions in a reasonable amount of time. In this paper a Genetic algorithm (GA) approach is used and for parameter tuning the Response Surface Method (RSM) is applied to increase the performance of the algorithm. Computational results show the high performance of the proposed algorithm to solve the generated problems.


Keywords


MSC


References