%0 Journal Article
%T Anti-predatory particle-swarm optimization with flexible inertial weight for unconstrained multilevel lot-sizing problems<br>多级生产批量规划问题的柔性惯量反捕食粒子群算法
%A HAN Yi
%A CAI Jian-hu
%A ZHOU Gen-gui
%A LI Yan-lai
%A TANG Jia-fu
%A <br>韩毅
%A 蔡建湖
%A 周根贵
%A 李延来
%A 唐加福
%J 控制理论与应用
%D 2010
%I 
%X Multilevel lot-sizing(MLLS) is a crucial problem in decision-making for the master production scheduling(MPP) of the material requirement plan(MRP), which is with broad industrial applications and has been considered the NP-hard combinatory optimization problem. Anti-predatory particle-swarm optimization(APSO), which is closely related to particle-swarm optimization(PSO), is a recently emerged meta-heuristics. An anti-predatory particle-swarm optimization with flexible inertial weight(WAPSO) is proposed to solve the unconstrained MLLS problem in a given assembly structure. A set of 12 small-sized benchmark data and a randomly generated medium size data are adopted to test the proposed algorithm. The experimental results are compared with those of genetic algorithm(GA) and Wagner-Whitin(WW) dynamic programming algorithm, the results show that WAPSO algorithm is an effective and suitable tool for solving the unconstrained MLLS problem in a given assembly structure.
%K multilevel lot-sizing
%K anti-predatory particle swarm optimization
%K meta-heuristics
%K inertial weight
%K assembly structure<br>多级生产批量规划
%K 反捕食粒子群算法
%K 亚启发式算法
%K 惯性权重
%K 装配结构
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=CCC58646964C2D7CAFB7661B5B06F1EE&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=F3090AE9B60B7ED1&sid=A903BA7BF48F47AE&eid=10F17081942653E7&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=0