Multi-objective optimization of stochastic disassembly line balancing with station paralleling

Authors:
Ayyuce Aydemir-Karadag;Orhan Turkbey
Affiliations:
Department of Logistics Management, Faculty of Business Administration, University of Turkish Aeronautical Association, Turkkusu Campus, 06790 Etimesgut, Ankara, Turkey;Department of Industrial Engineering, Faculty of Engineering, Gazi University, Maltepe, Ankara, Turkey
Venue:
Computers and Industrial Engineering
Year:
2013

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Abstract

One of the major activities performed in product recovery is disassembly. Disassembly line is the most suitable setting to disassemble a product. Therefore, designing and balancing efficient disassembly systems are important to optimize the product recovery process. In this study, we deal with multi-objective optimization of a stochastic disassembly line balancing problem (DLBP) with station paralleling and propose a new genetic algorithm (GA) for solving this multi-objective optimization problem. The line balance and design costs objectives are simultaneously optimized by using an AND/OR Graph (AOG) of the product. The proposed GA is designed to generate Pareto-optimal solutions considering two different fitness evaluation approaches, repair algorithms and a diversification strategy. It is tested on 96 test problems that were generated using the benchmark problem generation scheme for problems defined on AOG as developed in literature. In addition, to validate the performance of the algorithm, a goal programming approach and a heuristic approach are presented and their results are compared with those obtained by using GA. Computational results show that GA can be considered as an effective and efficient solution algorithm for solving stochastic DLBP with station paralleling in terms of the solution quality and CPU time.