Optimisation of cell configuration and comparisons using evolutionary computation approaches

被引：6

作者：

Dimopoulos, C ^{[1
]}

Zalzala, A ^{[1
]}

机构：

[1] Univ Sheffield, Dept Automat Control & Syst Engn, Sheffield S1 3JD, S Yorkshire, England

来源：

1998 IEEE INTERNATIONAL CONFERENCE ON EVOLUTIONARY COMPUTATION - PROCEEDINGS | 1998年

关键词：

cellular manufacturing; multi-objective optimisation; evolutionary computation;

D O I：

10.1109/ICEC.1998.699492

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper examines a cellular manufacturing optimisation problem in a new facility of a pharmaceutical company. The new facility, together with the old one, should be adequate to handle current and future production requirements. The aim of this paper is to investigate the potential use of evolutionary computation in order to find the optimum configuration of the cells in the facility. The objective is to maximise the total number of batches processed per year in the facility. In addition, a two-objective optimisation search was implemented, using several evolutionary computation methods. One additional objective is to minimise the overall cost, which is proportional to the number of cells in the facility. The multi-objective optimisation programs were based on three approaches: The weighted-sum approach, the Pareto-optimality approach, and the Multiobjective Genetic Algorithm (MOGA) approach.

引用

页码：148 / 153

页数：6