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title

Mixed-model two-side type II robotic assembly line balancing using particle swarm optimization with negative knowledge

Credit to Download: 1 | Page Numbers 11 | Abstract Views: 139
Year: 2017
COI code: IIEC14_043
Paper Language: English

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Authors Mixed-model two-side type II robotic assembly line balancing using particle swarm optimization with negative knowledge

a Zabihian - Department of Industrial Engineering, University of Tehran, Tehran, Iran
f jolai - Department of Industrial Engineering, University of Tehran, Tehran, Iran
m Rabbani - Department of Industrial Engineering, University of Tehran, Tehran, Iran
h Farrokhi-Asl - School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran

Abstract:

Assembly line balancing problem is one of most important problem for manufacturing process. In this paper, we consider a mixed-model two-side type II robotic assembly line balancing. Robot plays important role in assembly line balancing which has some advantage. Also, we consider a two-side line balancing that it uses for a large size and high volume of product, such as automobiles, trucks, and buses. In this paper, we consider 3 objective function that they should be minimize, the first one is setup cost of robots, the second one is purchasing robots cost and the last one is cycle time that we want to minimize them. Our problem in this paper is a NP-hard problem according our explanation. So, consider a mathematical model for solving them we consider two multi-objectives evolutionary algorithm. The first one is multi objective particle swarm optimization (MOPSO) and the second one is multi objective particle swarm optimization with negative knowledge (MOPSONK). At the end, we represent the result of ourproblem solving and we compare them together

Keywords:

Assembly line balancing; Mixed-model; Two-side; Multi-Objective Particle Swarm Optimization

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COI code: IIEC14_043

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Zabihian, a; f jolai; m Rabbani & h Farrokhi-Asl, 2017, Mixed-model two-side type II robotic assembly line balancing using particle swarm optimization with negative knowledge, 14th International Industrial Engineering Conference, تهران, انجمن مهندسي صنايع ايران - دانشگاه علم و صنعت ايران, https://www.civilica.com/Paper-IIEC14-IIEC14_043.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Zabihian, a; f jolai; m Rabbani & h Farrokhi-Asl, 2017)
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The University/Research Center Information:
Type: state university
Paper No.: 55403
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