论文信息 - Study on Line Balancing Problem Based on Improved Genetic Algorithms

Study on Line Balancing Problem Based on Improved Genetic Algorithms

An improved genetic algorithm is present for AIB problem, which uses a scaling fitness method, a stochastic universal sampling selection way, linear-changed crossbreed and mutation probabilities. The platform is achieved by PowerBuilder, the architecture and main data structure is also brought forth. The solution of AIB-2 problem is described by combining an example. It resolves the prematurity problem of simple genetic algorithms and greatly increases the performance of simple genetic algorithms.

Wang Yong | Zhang RuiJun | Yang ZhongHua | Chen DingFang | Wang XinXin

[1] Armin Scholl,et al. Maximizing the production rate in simple assembly line balancing -- A branch and bound procedure , 1996 .

[2] Yan Jun-qi. Appication of Genetic Algorithm Based on Task Sequences to Assembly Line Balancing , 2003 .

[3] Ihsan Sabuncuoglu,et al. Assembly line balancing using genetic algorithms , 2000, J. Intell. Manuf..

[4] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[5] Li Zhi. Improvement of Balance Problem of Assembly Line of Engine , 2004 .

[6] Armin Scholl,et al. Simple assembly line balancing—Heuristic approaches , 1997, J. Heuristics.

[7] Michael C. Ferris,et al. Genetic Algorithms for Combinatorial Optimization: The Assemble Line Balancing Problem , 1994, INFORMS J. Comput..

[8] Charles E. Taylor. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. Complex Adaptive Systems.John H. Holland , 1994 .

[9] Leendert Ammeraal,et al. Algorithms and data structures in C , 1996 .