Uniform Parallel Machine Scheduling with Dedicated Machines, Job Splitting and Setup Resources

Jun-Ho Lee,Hoon Jang

doi:10.3390/su11247137

Abstract

We examine a uniform parallel machine scheduling problem with dedicated machines, job splitting, and limited setup resources for makespan minimization. In this problem, machines have different processing speeds, and each job can only be processed at several designated machines. A job can be split into multiple sections and those sections can be processed on multiple machines simultaneously. Sequence-independent setup times are assumed, and setup operations between jobs require setup operators that are limited. For the problem, we first develop a mathematical optimization model and for large-sized problems a constructive heuristic algorithm is proposed. Finally, we show that the algorithm developed is efficient and provides good solutions by experiments with various scenarios.

Highlights

In recent manufacturing industries, increasing productivity and minimizing production costs are essential for a sustainable business
We consider a uniform parallel machine scheduling problem with dedicated machines, job splitting properties, and limited setup resources, which can be observed in practice
Since a uniform parallel machine scheduling problem with dedicated machines, job splitting, and setup resources is considered, relevant literature can be classified into three groups: studies considering parallel machines, job splitting, and resources

Summary

Introduction

In recent manufacturing industries, increasing productivity and minimizing production costs are essential for a sustainable business. We consider a uniform parallel machine scheduling problem with dedicated machines, job splitting properties, and limited setup resources, which can be observed in practice. FFUs or EFUs can be assembled in one of dedicated machines, and setups are performed when job types are changed, which are sequence-independent and require a setup operator. The problem considered in this paper has many real applications and is constrained by various scheduling requirements such as parallel machines with different speeds, dedicated machines, and limited setup operators. This paper is intended to contribute to this end by presenting a mathematical optimization model and developing efficient heuristic algorithms

Literature Review

Heuristic Algorithms

Experimental Results

Conclusions