结合Cat群算法和Firefly算法的云制造资源多目标调度

IF 2.8 3区工程技术 Q2 ENGINEERING, MANUFACTURING

Advances in Production Engineering & Management Pub Date : 2019-09-30 DOI:10.14743/apem2019.3.331

Y. Du, J. Wang, L. Lei

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引用次数: 13

摘要

本文试图使云制造资源的最大完工时间和成本最小化，并平衡过程调度的负担率。为此，建立了以最大完工时间最小、成本最小、负载均衡为目标的多目标调度模型。然后，将cat swarm optimization (CSO)和firefly algorithm (FA)结合成一种混合多目标调度算法。最后，通过CloudSim仿真对混合算法进行了验证。仿真结果表明，该算法能在短时间内输出最优调度方案。本研究不仅为多目标云制造资源过程调度问题在最短时间内找到全局最优解提供了有效途径，而且促进了群智能算法在作业车间调度问题中的应用。©2019马里博尔大学CPE。版权所有。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Multi-objective scheduling of cloud manufacturing resources through the integration of Cat swarm optimization and Firefly algorithm

This paper attempts to minimize the makespan and cost and balance the load rate of the process scheduling of cloud manufacturing resources. For this purpose, a multiobjective scheduling model was established to achieve the minimal makespan, minimal cost and balanced load rate. Next, the cat swarm optimization (CSO) and the firefly algorithm (FA) were combined into a hybrid multi -objective scheduling algorithm. Finally, the hybrid algorithm was verified through CloudSim simulation. The simulation resul ts show that the algori thm output the optimal scheduling pl an in a short time. This research not only provides an effective way to find the global optimal solution, within the shortest possible time, to the process scheduling problem of cloud manufacturing resources with multiple objectives, but also promotes the application of swarm intelligence algorithms in job-shop scheduling problems. © 2019 CPE, University of Maribor. All rights reserved.

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来源期刊

Advances in Production Engineering & Management ENGINEERING, MANUFACTURINGMATERIALS SCIENC-MATERIALS SCIENCE, MULTIDISCIPLINARY

CiteScore

5.90

自引率

22.20%

发文量

期刊介绍： Advances in Production Engineering & Management (APEM journal) is an interdisciplinary international academic journal published quarterly. The main goal of the APEM journal is to present original, high quality, theoretical and application-oriented research developments in all areas of production engineering and production management to a broad audience of academics and practitioners. In order to bridge the gap between theory and practice, applications based on advanced theory and case studies are particularly welcome. For theoretical papers, their originality and research contributions are the main factors in the evaluation process. General approaches, formalisms, algorithms or techniques should be illustrated with significant applications that demonstrate their applicability to real-world problems. Please note the APEM journal is not intended especially for studying problems in the finance, economics, business, and bank sectors even though the methodology in the paper is quality/project management oriented. Therefore, the papers should include a substantial level of engineering issues in the field of manufacturing engineering.