A Hybrid Genetic Algorithm for Flexible Job Shop Scheduling Problem With Sequence-Dependent Setup Times and Job Lag Times

Yilun Wang,Qianwen Zhu

doi:10.1109/access.2021.3096007

Yilun Wang, Qianwen Zhu

Open Access

https://doi.org/10.1109/access.2021.3096007

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Abstract

This paper addresses the flexible job shop scheduling problem with sequence-dependent set-up times and job lag times (FJSP-SDST-LT), which characteristics are important in modern manufacturing systems. We first present a mathematical model with the objective to minimize the makespan. Then a hybrid algorithm (HGA-TS) which combines genetic algorithm (GA) and tabu search (TS) is proposed to solve the FJSP-SDST-LT. The GA performs powerful global search by genetic operators and serves as exploration, while based on the specific structure of SDST and LT, the TS is able to perform an effective local search by relocating operations and serves as exploitation. Therefore, the proposed HGA-TS integrates good searching ability with strong diversifying ability. In order to solve the FJSP-SDST-LT effectively, we adopt effective encoding and decoding methods, genetic operators in GA, and four neighborhood structures in TS. We conduct computational experiments on two classes of instances generated from two classic data sets and the results show the great performance of HGA-TS in solving FJSP-SDST-LT.

Highlights

Production scheduling is one of the most critical optimization issues in the planning and managing of the modern manufacturing systems [1]
To evaluate the performance of the proposed HGA-tabu search (TS), we conduct experiments on two classes of FJSP-SDST-LT instances derived from benchmarks in [24], [30] respectively
The parameters including HGA-TS, pure genetic algorithm (GA), and TS for these instances are shown in Tables 1 and 2

Summary

Introduction

Production scheduling is one of the most critical optimization issues in the planning and managing of the modern manufacturing systems [1]. The flexible job shop scheduling problem(FJSP) was first presented by [2], which is one of the most prevalent problems, because it is widely applicable to real-world manufacturing systems. In many real applications such as chemical, semiconductor, pharmaceutical and automobile industry, setup time is incurred when two operations are successively processed in the same machine and lag time is incurred when an operation is finished and demands time of cooling down before the procedure [5]. In this case, the flexible job shop problem with

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