An iterated greedy algorithm for the large-scale unrelated parallel machines scheduling problem |
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Authors: | Francisco J. Rodriguez,Manuel Lozano,Christian Blum,Carlos Garcí a-Martí nez |
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Affiliation: | 1. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain;2. IKERBASQUE, Basque Foundation of Science, Bilbao, Spain;3. University of the Basque Country, San Sebastian, Spain;4. Department of Computing and Numerical Analysis, University of Córdoba, Córdoba, Spain |
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Abstract: | In this work, we tackle the problem of scheduling a set of jobs on a set of unrelated parallel machines with minimising the total weighted completion times as performance criteria. The iterated greedy metaheuristic generates a sequence of solutions by iterating over a constructive heuristic using destruction and construction phases. In the last few years, iterated greedy has been employed to solve a considerable number of problems. This is because it is based on a very simple principle, it is easy to implement, and it often exhibits an excellent performance. Moreover, scalability for high-dimensional problems becomes an essential requirement for modern optimisation algorithms. This paper proposes an iterated greedy model for the above-mentioned scheduling problem to tackle large-size instances. The benefits of our proposal in comparison to existing metaheuristics proposed in the literature are experimentally shown. |
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Keywords: | Iterated greedy Unrelated parallel machines Large-scale optimisation Scheduling |
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