IJAT Vol.17 No.1 pp. 71-80
doi: 10.20965/ijat.2023.p0071

Research Paper:

Scheduling Algorithm Using Path Relinking for Production Process with Crane Interference

Takashi Tanizaki*,†, Kazuya Yamada*, Shigemasa Nakagawa**, and Hideki Katagiri***

*Kindai University
1 Takaya-Umenobe, Higashi-Hiroshima, Hiroshima 739-2116, Japan

Corresponding author


***Faculty of Engineering, Kanagawa University, Yokohama, Japan

August 31, 2022
November 7, 2022
January 5, 2023
path relinking, scatter search, scheduling, crane interference, metaheuristics

In manufacturing industries, customers demand a wide variety of products, with high quality and fast delivery. Production scheduling systems have become critical for efficient operation. However, scheduling problems in manufacturing are generally large and complex with many constraints. It is difficult to create an optimal production schedule that satisfies all constraints within a reasonable timeframe. This study targets a factory with multiple working machines and two overhead cranes. Our research aims to obtain a solution algorithm to avoid interference of overhead cranes and machine competition and a production plan that minimizes the total makespan for each job. As the problem must be solved within a reasonable timeframe, we have developed the solution algorithm using metaheuristics and scheduling simulation. In general, metaheuristic algorithms must strike a balance between an intensive search for good solutions and a search for diverse solutions. Accordingly, we propose a new algorithm using path relinking in a scatter search. This method was demonstrated to be effective in obtaining good solutions with little variation in numerical experiments. In this paper, we describe previous research, our target process, and new solution algorithm and discuss algorithm design methods based on computer experiments.

Cite this article as:
T. Tanizaki, K. Yamada, S. Nakagawa, and H. Katagiri, “Scheduling Algorithm Using Path Relinking for Production Process with Crane Interference,” Int. J. Automation Technol., Vol.17 No.1, pp. 71-80, 2023.
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Last updated on May. 10, 2024