摘要
针对供应链环境下一类多目标Flow Shop调度问题,构建了相关模型并提出一种新的基于PSO、SOM和VNS的混合算法。该算法运用新的思想和多种优化策略,可在单个解的质量、解分布的均匀与分布的广度3个指标上同时达到远优于原算法的效果。仿真实验显示,该算法对求解该类调度问题十分有效。
This paper presents a model and a novel hybrid algorithm based on particle swarm optimization （PSO）, self organizing map（SOM） and variable neighborhood search（VNS） for a class of multi-objective Flow Shop scheduling problem under the environment of supply chain. The proposed algorithm can achieve better performance than original methods in terms of single solution quality, uniformity and range of solution distribution by applying new ideas and multiple optimization strategies. The effectiveness of the algorithm in solving the scheduling problem is demonstrated by numerical experiments.
出处
《合肥工业大学学报（自然科学版）》
CAS
CSCD
北大核心
2011年第10期1564-1569,1583,共7页
Journal of Hefei University of Technology：Natural Science
基金
安徽省高等学校省级自然科学研究重点资助项目(KJ0211A215)
合肥工业大学博士学位专项基金资助项目(GDBJ2010-001)
关键词
多目标
供应链
FLOW
Shop调度问题
自组织神经网络算法
粒子群
变邻域搜索
multi-objective
supply chain
Flow Shop scheduling problem
self organizing map（SOM）algorithm
particle swarm
variable neighborhood search（VNS）
