INEH-VNS Algorithm Solved Automatic Production System Scheduling Problem under Just-in-Time Environment

Automatic production system scheduling problem under a just-in-time environment is researched in this paper. The automatic production system is composed of many tanks and one robotic, the tank of the researched problem is responsible for processing the job, and the robotic moves the job from one tan...

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Main Authors: Li Qingxiang, Zhao Xiaofei, He Yude, Yin Shaojun
Format: Article
Language:English
Published: Wiley 2023-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2023/6680897
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author Li Qingxiang
Zhao Xiaofei
He Yude
Yin Shaojun
author_facet Li Qingxiang
Zhao Xiaofei
He Yude
Yin Shaojun
author_sort Li Qingxiang
collection DOAJ
description Automatic production system scheduling problem under a just-in-time environment is researched in this paper. The automatic production system is composed of many tanks and one robotic, the tank of the researched problem is responsible for processing the job, and the robotic moves the job from one tank to the other tank. The difference between the researched problem and the classic shop scheduling problem is that the former must consider job scheduling and the robotic move sequence, but the latter considers only job scheduling. For optimizing simultaneously job scheduling and robotic move sequence in the proposed problem and minimizing total earliness/tardiness, an improved NEH (Nawaz-Enscore-Ham) and variable search (INEH-VNS) algorithm are developed. In the proposed method, firstly, to obtain initial solution, an improved NEH is shown. Secondly, for computing value of the objective function, the double procedure method is constructed. Thirdly, according to the properties of the proposed problem, three neighborhood structures, adjacent exchange, random insertion, and job exchange, are investigated. To test the performance of the INEH-VNS, 100 instances are randomly generated. When the run time is the same, compared with CPLEX 12.5, the INEH-VNS algorithm can find high-quality approximate optimal solution, a special big scale. Compared with the G-VNS algorithm, the average improvement rate of the approximate optimal solution is 45.9%, and the average stability rate of the INEH-VNS algorithm enhances 75.04%. That is to say, the INEH-VNS algorithm is outstanding and more effective.
format Article
id doaj-art-607e3577dfab40d3badd9603bb53a397
institution Kabale University
issn 1687-0042
language English
publishDate 2023-01-01
publisher Wiley
record_format Article
series Journal of Applied Mathematics
spelling doaj-art-607e3577dfab40d3badd9603bb53a3972025-08-20T03:34:48ZengWileyJournal of Applied Mathematics1687-00422023-01-01202310.1155/2023/6680897INEH-VNS Algorithm Solved Automatic Production System Scheduling Problem under Just-in-Time EnvironmentLi Qingxiang0Zhao Xiaofei1He Yude2Yin Shaojun3College of Artificial IntelligenceSchool of Economics and ManagementSchool of ManagementCollege of ScienceAutomatic production system scheduling problem under a just-in-time environment is researched in this paper. The automatic production system is composed of many tanks and one robotic, the tank of the researched problem is responsible for processing the job, and the robotic moves the job from one tank to the other tank. The difference between the researched problem and the classic shop scheduling problem is that the former must consider job scheduling and the robotic move sequence, but the latter considers only job scheduling. For optimizing simultaneously job scheduling and robotic move sequence in the proposed problem and minimizing total earliness/tardiness, an improved NEH (Nawaz-Enscore-Ham) and variable search (INEH-VNS) algorithm are developed. In the proposed method, firstly, to obtain initial solution, an improved NEH is shown. Secondly, for computing value of the objective function, the double procedure method is constructed. Thirdly, according to the properties of the proposed problem, three neighborhood structures, adjacent exchange, random insertion, and job exchange, are investigated. To test the performance of the INEH-VNS, 100 instances are randomly generated. When the run time is the same, compared with CPLEX 12.5, the INEH-VNS algorithm can find high-quality approximate optimal solution, a special big scale. Compared with the G-VNS algorithm, the average improvement rate of the approximate optimal solution is 45.9%, and the average stability rate of the INEH-VNS algorithm enhances 75.04%. That is to say, the INEH-VNS algorithm is outstanding and more effective.http://dx.doi.org/10.1155/2023/6680897
spellingShingle Li Qingxiang
Zhao Xiaofei
He Yude
Yin Shaojun
INEH-VNS Algorithm Solved Automatic Production System Scheduling Problem under Just-in-Time Environment
Journal of Applied Mathematics
title INEH-VNS Algorithm Solved Automatic Production System Scheduling Problem under Just-in-Time Environment
title_full INEH-VNS Algorithm Solved Automatic Production System Scheduling Problem under Just-in-Time Environment
title_fullStr INEH-VNS Algorithm Solved Automatic Production System Scheduling Problem under Just-in-Time Environment
title_full_unstemmed INEH-VNS Algorithm Solved Automatic Production System Scheduling Problem under Just-in-Time Environment
title_short INEH-VNS Algorithm Solved Automatic Production System Scheduling Problem under Just-in-Time Environment
title_sort ineh vns algorithm solved automatic production system scheduling problem under just in time environment
url http://dx.doi.org/10.1155/2023/6680897
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