Title :
Optimisation of cell configuration and comparisons using evolutionary computation approaches
Author :
Dimopoulos, C. ; Zalzala, AMS
Author_Institution :
Dept. of Autom. Control & Syst. Eng., Sheffield Univ., UK
Abstract :
The 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 the 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, 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 multi-objective genetic algorithm (MOGA) approach
Keywords :
batch processing (industrial); genetic algorithms; pharmaceutical industry; search problems; Pareto-optimality approach; cell configuration optimisation; cellular manufacturing optimisation problem; evolutionary computation; maximised batch number; multi-objective genetic algorithm; new facility; overall cost minimisation; pharmaceutical company; two-objective optimisation search; weighted-sum approach; Cellular manufacturing; Cost function; Evolutionary computation; Genetic algorithms; Group technology; Inductors; Optimization methods; Pharmaceuticals; Production; Systems engineering and theory;
Conference_Titel :
Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4869-9
DOI :
10.1109/ICEC.1998.699492
