Genetic Algorithm Approach to a Scheduling Problem for a Metal Mold Assembly Process

Abstract

This paper deals with a large-scale scheduling problem for a metal mold assembly process of automatic vending machines, which is based on a job shop process with additional conditions such as precedence constraints among jobs, parallel machines, and introduction of multi-function machines. The objective of the problem is to minimize the sum of the tardiness of each product. The genetic algorithm (GA) is applied to this problem. Particularly, a method for generating initial individuals and a mutation procedure are proposed. It is observed through simulations for a real data that GA is more effective than a heuristic method.