An approach to multi-criteria assembly sequence planning using genetic algorithms

@article{citeulike:3013879, abstract = {Abstract\ \ This paper focuses on multi-criteria assembly sequence planning (ASP) known as a large-scale, time-consuming combinatorial problem. Although the ASP problem has been tackled via a variety of optimization techniques, these techniques are often inefficient when applied to larger-scale problems. Genetic algorithm (GA) is the most widely known type of evolutionary computation method, incorporating biological concepts into analytical studies of systems. In this research, an approach is proposed to optimize multi-criteria ASP based on GA. A precedence matrix is proposed to determine feasible assembly sequences that satisfy precedence constraints. A numerical example is presented to demonstrate the performance of the proposed algorithm. The results of comparison in the provided experiment show that the developed algorithm is an efficient approach to solve the ASP problem and can be suitably applied to any kind of ASP with large numbers of components and multi-objective functions.}, author = {Choi, Young-Keun and Lee, Dong and Cho, Yeong }, citeulike-article-id = {3013879}, doi = {http://dx.doi.org/10.1007/s00170-008-1576-4}, journal = {The International Journal of Advanced Manufacturing Technology}, keywords = {evolutionary-computation, genetic-algorithm, metaheuristic, multi-objective, planning}, posted-at = {2008-07-17 09:40:34}, priority = {2}, title = {An approach to multi-criteria assembly sequence planning using genetic algorithms}, url = {http://dx.doi.org/10.1007/s00170-008-1576-4} }

TY - JOUR ID - citeulike:3013879 L3 - citeulike-article-id:3013879 TI - An approach to multi-criteria assembly sequence planning using genetic algorithms JF - The International Journal of Advanced Manufacturing Technology N2 - Abstract  This paper focuses on multi-criteria assembly sequence planning (ASP) known as a large-scale, time-consuming combinatorial problem. Although the ASP problem has been tackled via a variety of optimization techniques, these techniques are often inefficient when applied to larger-scale problems. Genetic algorithm (GA) is the most widely known type of evolutionary computation method, incorporating biological concepts into analytical studies of systems. In this research, an approach is proposed to optimize multi-criteria ASP based on GA. A precedence matrix is proposed to determine feasible assembly sequences that satisfy precedence constraints. A numerical example is presented to demonstrate the performance of the proposed algorithm. The results of comparison in the provided experiment show that the developed algorithm is an efficient approach to solve the ASP problem and can be suitably applied to any kind of ASP with large numbers of components and multi-objective functions. KW - evolutionary-computation KW - genetic-algorithm KW - metaheuristic KW - multi-objective KW - planning AU - Choi, Young-Keun AU - Lee, Dong AU - Cho, Yeong UR - http://dx.doi.org/10.1007/s00170-008-1576-4 ER -