Manuel Chica, Oscar Cordon, Sergio Damas, Joaquin Bautista
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ABSTRACT: In this work we present two new multiobjective proposals based on ant colony optimisation and random greedy search algorithms to solve a more realistic extension of a classical industrial problem: time and space assembly line balancing. Some variants of these algorithms have been compared in order to find out the impact of different design configurations and the use of heuristic information. Good performance is shown after applying every algorithm to 10 well-known problem instances in comparison to NSGA-II. In addition, those algorithms which have provided the best results have been employed to tackle a real-world problem at the Nissan plant, located in Spain.
Information Sciences 01/2010; 180(18):3465-3487. · 2.83 Impact Factor
