An Implementation of Flexible Job Shop Scheduling Problem in a Metal Processing Company

Abstract

In this study we consider the flexible job-shop scheduling problem at a local metal sheet processing company. We aim to develop a model and an algorithm to generate a weekly production plan for the company. The objective is to minimize the makespan while meeting the demands of products for a given planning horizon. First we provide an LP formulation of this problem. The computational complexity of the problem is NP-hard hence the input data prohibits obtaining the optimal solution in a reasonable time. Therefore we implement a metaheuristic and several rule-based heuristics. These are Genetic Algorithm Giffler and Thompson’s Algorithm and three other Rule-Based Heuristic Algorithms that we developed. We first test our model and heuristics over a set of sample instances then we solve for the real data. Our experimental study indicates that one of the rule-based heuristics we developed outperforms others in most of the instances. © 2020 Elsevier B.V. All rights reserved.