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GRASP Applied to Multi–Skill Resource–Constrained Project Scheduling Problem

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Computational Collective Intelligence (ICCCI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9875))

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Abstract

The paper describes an application of Greedy Randomized Adaptive Search Procedure (GRASP) in solving Multi–Skill Resource-Constrained Project Scheduling Problem (MS-RCPSP). Proposed work proposes a specific greedy–based local search and schedule constructor specialised to MS-RCPSP. The GRASP is presented as the better option to classical heuristic but also as a faster and successful alternative to another metaheuristic. To compare results of GRASP to others approaches, various methods are proposed: methods of constructing scheduling based on the greedy algorithm, randomized greedy approach, and HAntCO. The research was performed using all instances of benchmark iMOPSE dataset and the results compared to best–known methods.

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Notes

  1. 1.

    parameter \(alpha=0.3\) used in RGB procedure was established experimentally.

  2. 2.

    All best found GRASP solutions we published on iMOPSE project homepage: http://imopse.ii.pwr.edu.pl.

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Authors and Affiliations

  1. Department of Computational Intelligence, Wrocław University of Technology, Wrocław, Poland

    Paweł B. Myszkowski & Jȩdrzej J. Siemieński

Authors
  1. Paweł B. Myszkowski
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  2. Jȩdrzej J. Siemieński
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Corresponding author

Correspondence to Paweł B. Myszkowski .

Editor information

Editors and Affiliations

  1. Wrocław University of Technology, Wrocław, Poland

    Ngoc-Thanh Nguyen

  2. Aristotle University of Thessaloniki, Thessaloniki, Greece

    Lazaros Iliadis

  3. Department of Forestry and Management, Democritus University of Thrace, Orestiada, Thrace, Greece

    Yannis Manolopoulos

  4. Wrocław University of Technology, Wrocław, Poland

    Bogdan Trawiński

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© 2016 Springer International Publishing Switzerland

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Myszkowski, P.B., Siemieński, J.J. (2016). GRASP Applied to Multi–Skill Resource–Constrained Project Scheduling Problem. In: Nguyen, NT., Iliadis, L., Manolopoulos, Y., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2016. Lecture Notes in Computer Science(), vol 9875. Springer, Cham. https://doi.org/10.1007/978-3-319-45243-2_37

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  • DOI: https://doi.org/10.1007/978-3-319-45243-2_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45242-5

  • Online ISBN: 978-3-319-45243-2

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