Journal
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volume 25, Issue 2, Pages 254-273Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engappai.2011.05.001
Keywords
Time and space assembly line balancing problem; Automotive industry; Multiobjective optimisation; Memetic algorithms; NSGA-II; Ant colony optimisation; GRASP; Local search
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Funding
- UPC Nissan Chair
- Spanish Ministerio de Educacion y Ciencia [DPI2010-16759]
- Spanish Ministerio de Ciencia e Innovacion [TIN2009-07727]
- EDRF
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This paper presents three proposals of multiobjective memetic algorithms to solve a more realistic extension of a classical industrial problem: time and space assembly line balancing. These three proposals are, respectively, based on evolutionary computation, ant colony optimisation, and greedy randomised search procedure. Different variants of these memetic algorithms have been developed and compared in order to determine the most suitable intensification-diversification trade-off for the memetic search process. Once a preliminary study on nine well-known problem instances is accomplished with a very good performance, the proposed memetic algorithms are applied considering real-world data from a Nissan plant in Barcelona (Spain). Outstanding approximations to the pseudo-optimal non-dominated solution set were achieved for this industrial case study. (C) 2011 Elsevier Ltd. All rights reserved.
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