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Local Search Methods for the MRCPSP-Energy

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Hybrid Metaheuristics (HM 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11299))

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Abstract

The Multi-Mode Resource-Constrained Project Scheduling Problem with energy saving (MRCPSP-energy) is a variant of the classical Resource-Constrained Project Scheduling Problem (RCPSP). In this variant, the execution of each job must take into account the job duration and the energy spent to execute that job, which are conflicting. The objective is to minimize both makespan and total energy consumption. This work proposes two local search methods to improve a large dataset of inputs. One of them is a restricted version of a Mixed-Integer Programming formulation and the other one is a heuristic local search called H. The computational experiments showed that the hybrid method with the H algorithm obtained better solutions and is competitive with the literature results.

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Authors and Affiliations

  1. Institute of Science and Technology, Federal Fluminense University, Rio das Ostras, Brazil

    André Renato Villela da Silva

  2. Institute of Computing, Federal Fluminense University, Niterói, Brazil

    Luiz Satoru Ochi

Authors
  1. André Renato Villela da Silva
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  2. Luiz Satoru Ochi
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Corresponding author

Correspondence to André Renato Villela da Silva .

Editor information

Editors and Affiliations

  1. Universitat Politècnica de Catalunya, Barcelona, Spain

    Maria J. Blesa Aguilera

  2. Spanish National Research Council, Bellaterra, Spain

    Christian Blum

  3. Universidade Federal de Ouro Preto, Ouro Preto, Brazil

    Haroldo Gambini Santos

  4. University of Concepción, Concepción, Chile

    Pedro Pinacho-Davidson

  5. Universidad de Concepción, Concepción, Chile

    Julio Godoy del Campo

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Villela da Silva, A.R., Satoru Ochi, L. (2019). Local Search Methods for the MRCPSP-Energy. In: Blesa Aguilera, M., Blum, C., Gambini Santos, H., Pinacho-Davidson, P., Godoy del Campo, J. (eds) Hybrid Metaheuristics. HM 2019. Lecture Notes in Computer Science(), vol 11299. Springer, Cham. https://doi.org/10.1007/978-3-030-05983-5_13

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  • DOI: https://doi.org/10.1007/978-3-030-05983-5_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05982-8

  • Online ISBN: 978-3-030-05983-5

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