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

Li Qingxiang, Zhao Xiaofei, He Yude and Yin Shaojun

Journal of Applied Mathematics, 2023, vol. 2023, issue 1

Abstract: 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.

Date: 2023
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https://doi.org/10.1155/2023/6680897

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Persistent link: https://EconPapers.repec.org/RePEc:wly:jnljam:v:2023:y:2023:i:1:n:6680897

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