Multi-criteria Optimization Evolving Artificial Ants as a Computational Intelligence Technique

摘要：

This paper presents the application Ant Colony Optimization (ACO) to solve multi-criteria combinatorial optimization problems. The proposed decision support technique is validated on the Hybrid Flowshop Scheduling Problem with minimization of both the makespan and the total completion time of jobs. This problem is considered to be strongly NP-hard and has been little studied literature. Our algorithm is compared against other well-known heuristics from the literature adapted to solve this problem and experimental results show that our algorithm outperforms them.

关键词： Multi-criteria Optimization Ant Colony Meta-Heuristics Hybrid Flowshop

作者: Elyn L Solano Charris Jairo R.Montoya-Torres Carlos D.Paternina-Arboleda

作者单位: Escuela de Ciencias Economicas y Administrativas Universidad del la Sabana Bogotá D.C.,Chia (Cundina Departamento de Tngenieria Industrial Universidad del Norte Barranquilla,Colombia

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 1618-1622

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）