Including different kinds of preferences in a multi-objective ant algorithm for time and space assembly line balancing on different Nissan scenarios

Authors:
Manuel Chica;Oscar Cordón;Sergio Damas;Joaquín Bautista
Affiliations:
European Centre for Soft Computing, 33600 Mieres, Spain;European Centre for Soft Computing, 33600 Mieres, Spain;European Centre for Soft Computing, 33600 Mieres, Spain;Nissan Chair - Universitat Politècnica de Catalunya, Barcelona, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

Most of the decision support systems for balancing industrial assembly lines are designed to report a huge number of possible line configurations, according to several criteria. In this contribution, we tackle a more realistic variant of the classical assembly line problem formulation, time and space assembly line balancing. Our goal is to study the influence of incorporating user preferences based on Nissan automotive domain knowledge to guide the multi-objective search process with two different aims. First, to reduce the number of equally preferred assembly line configurations (i.e., solutions in the decision space) according to Nissan plants requirements. Second, to only provide the plant managers with configurations of their contextual interest in the objective space (i.e., solutions within their preferred Pareto front region) based on real-world economical variables. We face the said problem with a multi-objective ant colony optimisation algorithm. Using the real data of the Nissan Pathfinder engine, a solid empirical study is carried out to obtain the most useful solutions for the decision makers in six different Nissan scenarios around the world.