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We present an extension of a multi-objective algorithm based on Ant Colony Optimisation to solve a more realistic variant of a classical industrial problem: Time and Space Assembly Line Balancing. We study the influence of incorporating some domain knowledge by guiding the search process of the algorithm with preferences-based dominance. Our
approach is compared with other techniques, and every algorithm tackles a real-world instance from a Nissan plant. We prove that the embedded expert knowledge is even more justified in a real-world problem.
CitationChica, M. [et al.]. Incorporating preferences to a multi-objective ant colony algorithm for time and space assembly line balancing. A: "Lecture Notes in Computer Science - Ant Colony Optimization and Swarm Intelligence. Volume 5217/2008". Springer, 2008, p. 331-338.
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