A bi-objective Optimization Model for a Dynamic Cell Formation Integrated with Machine and Cell Layouts in a Fuzzy Environment

IF 1.3 Q2 MATHEMATICS, APPLIED Fuzzy Information and Engineering Pub Date : 2020-04-02 DOI:10.1080/16168658.2020.1747162
A. Golmohammadi, Mahnoobeh Honarvar, H. Hosseini-nasab, R. Tavakkoli-Moghaddam
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引用次数: 15

Abstract

In this paper, a bi-objective optimization model is developed to integrate the cell formation and inter/intra-cell layouts in continuous space by considering fuzzy conditions to minimize the total cost of parts relocations as well as cells reconfigurations. The intra- and inter-cell movements for both parts and machines using batch sizes for transferring parts are related to the distance traveled through a rectilinear distance in a fuzzy environment. To solve the proposed problem as a bi-objective mixed-integer non-linear programming model is NP-hard, four meta-heuristic algorithms based on a multi-objective optimization structure are tackled to address the problem. In this regard, not only Genetic Algorithm (GA), Keshtel Algorithm (KA) and Red Deer Algorithm (RDA) are employed to solve the problem, but also a novel hybrid meta-heuristic algorithm based on the benefits of aforementioned algorithms is developed. Finally, by considering some efficient assessment metrics of Pareto-based algorithms, the results indicate that the proposed hybrid algorithm not only is more appropriate than the exact solver but it also outperforms the performance of individual ones particularly in medium- and large-sized problems.
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模糊环境下结合机器和细胞布局的动态细胞编队双目标优化模型
本文通过考虑模糊条件,建立了一种双目标优化模型,将连续空间中的单元形成和单元间/单元内布局整合在一起,以最小化部件重新定位和单元重新配置的总成本。在模糊环境中,零件和机器在单元内和单元间的运动与通过直线距离的距离有关。为了解决双目标混合整数非线性规划模型的np困难问题,采用了基于多目标优化结构的四种元启发式算法来解决该问题。在此基础上,采用遗传算法(GA)、Keshtel算法(KA)和Red Deer算法(RDA)进行求解,并结合上述算法的优点,提出了一种新的混合元启发式算法。最后,通过考虑基于pareto算法的一些有效的评估指标,结果表明所提出的混合算法不仅比精确求解器更合适,而且在大中型问题上优于单个算法的性能。
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来源期刊
CiteScore
2.30
自引率
0.00%
发文量
13
审稿时长
40 weeks
期刊介绍: Fuzzy Information and Engineering—An International Journal wants to provide a unified communication platform for researchers in a wide area of topics from pure and applied mathematics, computer science, engineering, and other related fields. While also accepting fundamental work, the journal focuses on applications. Research papers, short communications, and reviews are welcome. Technical topics within the scope include: (1) Fuzzy Information a. Fuzzy information theory and information systems b. Fuzzy clustering and classification c. Fuzzy information processing d. Hardware and software co-design e. Fuzzy computer f. Fuzzy database and data mining g. Fuzzy image processing and pattern recognition h. Fuzzy information granulation i. Knowledge acquisition and representation in fuzzy information (2) Fuzzy Sets and Systems a. Fuzzy sets b. Fuzzy analysis c. Fuzzy topology and fuzzy mapping d. Fuzzy equation e. Fuzzy programming and optimal f. Fuzzy probability and statistic g. Fuzzy logic and algebra h. General systems i. Fuzzy socioeconomic system j. Fuzzy decision support system k. Fuzzy expert system (3) Soft Computing a. Soft computing theory and foundation b. Nerve cell algorithms c. Genetic algorithms d. Fuzzy approximation algorithms e. Computing with words and Quantum computation (4) Fuzzy Engineering a. Fuzzy control b. Fuzzy system engineering c. Fuzzy knowledge engineering d. Fuzzy management engineering e. Fuzzy design f. Fuzzy industrial engineering g. Fuzzy system modeling (5) Fuzzy Operations Research [...] (6) Artificial Intelligence [...] (7) Others [...]
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