A hybrid genetic algorithm for solving machine layout problem with consideration of industrial constraints

摘要

This paper focuses on loop layout problem in flexible manufacturing systems using one load and unload machine. The objective of this problem is to determine the ordering of machines around a loop, to minimize the total cost of transporting parts within each manufacturing cell. The novelty of this study lies on the reformulation of the problem while taking into account new variables generally neglected by recent researches like proximity constraints and machine dimensions. Hence, we aim to place these machines on a grid that represents the surface of the cell, in order to construct a loop layout while respecting proximity constraints. And as objective, we try to minimize the total cost of transporting parts within each manufacturing cell. This new formulation led us to propose a two-stage approach to solve this problem. The first step consists in positioning the machines on a grid while respecting the proximity constraints and machines dimensions. The second step aims to optimize the path between these machines already positioned in order to minimize number of the loops travelled by parts. In this paper, we are interested in the second step. To solve this problem, we use genetic algorithms. This choice is motivated by the well-known of the efficiency of genetic algorithms to solve quadratic assignment problems. Hence, we proposed three hybrid genetic algorithms. The effectiveness of our approaches is demonstrated through numerical examples.