Multi-objective two-sided mixed-model assembly line balancing using particle swarm optimisation with negative knowledge

Chutima, Parames; Chimklai, Palida

doi:10.1016/j.cie.2011.08.015

Cited by 120 publications

(56 citation statements)

References 35 publications

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“…Meta-heuristics have also been presented to address twosided assembly line balancing problem, i.e. Baykasoglu and Dereli (2008), Simaria and Vilarinho (2009), Ozcan and Toklu (2009b), Ozbakir and Tapkan (2010), Ozcan (2010), Ozbakir and Tapkan (2011), Chutima and Chimklai (2012). Among these meta-heuristics, the studies of Kim et al (2000Kim et al ( , 2009, Taha et al (2011), Purnomo et al (2013), and Rabbani et al (2012) employ different variations of genetic algorithm to balance two-sided lines.…”

Section: International Journal Of Production Researchmentioning

confidence: 99%

Simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Küçükkoç

Zhang

2014

International Journal of Production Research

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Growing interests from customers in customised products and increasing competitions among peers necessitate companies to configure their manufacturing systems more effectively than ever before. We propose a new assembly line system configuration for companies that need intelligent solutions to satisfy customised demands on time with existing resources. A mixed-model parallel two-sided assembly line system is introduced based on the parallel two-sided assembly line system previously proposed by Ozcan et al. (Balancing parallel two-sided assembly lines, International Journal of Production Research, 48 (16), 4767-4784, 2010). The mixed-model parallel two-sided assembly line balancing problem is illustrated with examples from the perspective of simultaneous balancing and sequencing. An agent based ant colony optimisation algorithm is proposed to solve the problem. This algorithm is the first attempt in the literature to solve an assembly line balancing problem with an agent based ant colony optimisation approach. The algorithm is illustrated with an example and its operational procedures and principles explained and discussed.Keywords: mixed-model parallel two-sided assembly lines; assembly line balancing; agent based ant colony optimisation; meta-heuristics; artificial intelligence

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Section: International Journal Of Production Researchmentioning

confidence: 99%

Simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Küçükkoç

Zhang

2014

International Journal of Production Research

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“…Then, Ozcan et al (2011) and Hamzadayi and Yildiz (2012) proposed different genetic algorithm based approaches for balancing and sequencing of U-shaped lines simultaneously; by considering stochastic times, and parallel workstations -zoning constraints, respectively. Ozcan et al (2010b) and Kucukkoc and Zhang (2013) Simaria and Vilarinho (2009), Ozcan and Toklu (2009), and Chutima and Chimklai (2012 since there is no opportunity to utilise contrary stations (as in U-lines) or multi-line stations (as in parallel lines) and model mixes are not important unless a setup operation is required when changing from one model to another. However, Rabbani et al (2012) proposed multiple U-shaped layout to deal with mixed-model two-sided assembly line balancing problem and utilised contrary workstations.…”

Section: Literature Reviewmentioning

confidence: 99%

Mathematical model and agent based solution approach for the simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Küçükkoç

Zhang

2014

International Journal of Production Economics

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Cite this article as: Ibrahim Kucukkoc, David Z. Zhang, Mathematical model and agent based solution approach for the simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines, Int. J. Production Economics, http://dx.doi.org/10.1016/j.ijpe. 2014.08.010 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. AbstractOne of the key factors of a successfully implemented mixed-model line system is considering model sequencing problem as well as the line balancing problem. In the literature, there are many studies, which consider these two tightly interrelated problems individually. However, we integrate the model sequencing problem in the line balancing procedure to obtain a more efficient solution for the problem of Simultaneous Balancing and Sequencing of Mixed-Model Parallel Two-Sided AssemblyLines. A mathematical model is developed to present the problem and a novel agent based ant colony optimisation approach is proposed as the solution method. Different agents interact with each other to find a near optimal solution for the problem. Each ant selects a random behaviour from a predefined list of heuristics and builds a solution using this behaviour as a local search rule along with the pheromone value. Different cycle times are allowed for different two-sided lines located in parallel to each other and this yields a complex problem where different production cycles need to be considered to build a feasible solution. The performance of the proposed approach is tested through a set of test cases. Experimental results indicate that considering model sequencing problem with the line balancing problem together helps minimise line length and total number of required workstations. Also, it is found that the proposed approach outperforms other three heuristics tested.Keywords: mixed-model parallel two-sided assembly lines; simultaneous line balancing and model sequencing; agent based ant colony optimisation; production lines; metaheuristics; artificial intelligence. Experimental results indicate that considering model sequencing problem with the line balancing problem together helps minimise line length and total number of required workstations. Also, it is found that the proposed approach outperforms other three heuristics tested.

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“…They resulted in optimizing cycle time and the number of stations. Chutima and Chimklai [13] worked on multi-objective two-sided mixed-model assembly line balancing using particle swarm optimization with negative knowledge. They were able to minimize the cycle time, minimize total cost, and the smoothness index.…”

Section: Introductionmentioning

confidence: 99%

Assembly Line Balancing Using Fuzzy Logic: A Case Study of a Tricycle Assembly Line

Unuigbe¹,

Aigboje²,

Ehizibue³

2016

OJOp

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The application of fuzzy logic in balancing a single model tricycle assembly line is presented in this study. MATLAB simulation software was used in the analysis of the primary and secondary data obtained from the assembly line under study. Results obtained from the study show that the efficiency of the line increased from 88.1% to 92.4%. The total idle time was also reduced by 56.5%. This indicates an improvement in the efficiency of the line, reduction of bottleneck, and even distribution of tasks along the line for the company under study.

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Multi-objective two-sided mixed-model assembly line balancing using particle swarm optimisation with negative knowledge

Cited by 120 publications

References 35 publications

Simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Mathematical model and agent based solution approach for the simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Assembly Line Balancing Using Fuzzy Logic: A Case Study of a Tricycle Assembly Line

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