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APPLICATION OF INTEGER CODING ACCELERATING GENETIC ALGORITHM IN RECTANGULAR CUTTING STOCK PROBLEM 被引量:3
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作者 FANG Hui YIN Guofu LI Haiqing PENG Biyou 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2006年第3期335-339,共5页
An improved genetic algorithm and its application to resolve cutting stock problem arc presented. It is common to apply simple genetic algorithm (SGA) to cutting stock problem, but the huge amount of computing of SG... An improved genetic algorithm and its application to resolve cutting stock problem arc presented. It is common to apply simple genetic algorithm (SGA) to cutting stock problem, but the huge amount of computing of SGA is a serious problem in practical application. Accelerating genetic algorithm (AGA) based on integer coding and AGA's detailed steps are developed to reduce the amount of computation, and a new kind of rectangular parts blank layout algorithm is designed for rectangular cutting stock problem. SGA is adopted to produce individuals within given evolution process, and the variation interval of these individuals is taken as initial domain of the next optimization process, thus shrinks searching range intensively and accelerates the evaluation process of SGA. To enhance the diversity of population and to avoid the algorithm stagnates at local optimization result, fixed number of individuals are produced randomly and replace the same number of parents in every evaluation process. According to the computational experiment, it is observed that this improved GA converges much sooner than SGA, and is able to get the balance of good result and high efficiency in the process of optimization for rectangular cutting stock problem. 展开更多
关键词 Accelerating genetic algorithm Efficiency of optimization cutting stock problem
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