An Evolutionary Approach for the Design and Scheduling of Electroplating Facilities

Abstract

This paper tackles the Cyclic Hoists Scheduling Problem. This problem is often encountered in electroplating facilities when mass production is required. Then a repetitive sequence of moves is searched for the hoists. We more precisely deal with a global optimization problem that simultaneously considers the design and the scheduling of such production lines. It consists in studying systems integrating several transportation resources, called hoists, by minimizing the cycle time, while minimizing the number of hoists used. To achieve these goals, we use an evolutionary approach. The encoding of one solution is based on the representation of the empty moves of the hoists. To evaluate each individual, we propose a linear programming model. This one both verifies the satisfaction of constraints and provides the best cycle time for the considered number of hoists. This contribution describes a promising approach to solving a simple version of this problem, namely cyclic hoist scheduling, based on Evolutionary Algorithms (EAs), which is an optimization method inspired by biological evolution models. The issues of solution encoding and specialised genetic operators with a repair procedure of the infeasible solutions are discussed. Some results are presented with benchmark examples.