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An Improved Genetic Algorithm for the Resource-Constrained Project Scheduling Problem

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Advances in Optimization and Applications (OPTIMA 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1739))

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Abstract

This paper presents an improved genetic algorithm for the Resource Constrained Project Scheduling Problem (RCPSP). The schedules are constructed using a heuristic that builds active schedules based on priorities that takes into account the degree of criticality for the resources. The degree of resource’s criticality is derived from the solution of a relaxed problem with a constraint on accumulative resources. The computational results with instances from the PCPLIB library validate the effectiveness of the proposed algorithm. We have obtain some of the best average deviations of the solutions from the critical path value. The best known solutions have been improved for some instances from the PCPLIB.

The study was carried out within the framework of the state contract of the Sobolev Institute of Mathematics (project FWNF-2022-0019).

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Author information

Authors and Affiliations

  1. Sobolev Institute of Mathematics, Prosp. Akad. Koptyuga, 4, Novosibirsk, Russia

    Evgenii N. Goncharov

  2. Novosibirsk State University, str. Pirogova, 1, Novosibirsk, Russia

    Evgenii N. Goncharov

Authors
  1. Evgenii N. Goncharov
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Correspondence to Evgenii N. Goncharov .

Editor information

Editors and Affiliations

  1. FRC CSC RAS, Moscow, Russia

    Nicholas Olenev

  2. FRC CSC RAS, Moscow, Russia

    Yuri Evtushenko

  3. University of Montenegro, Podgorica, Montenegro

    Milojica Jaćimović

  4. Krasovsky Institute of Mathematics and Mechanics, Ekaterinburg, Russia

    Michael Khachay

  5. FRC CSC RAS, Moscow, Russia

    Vlasta Malkova

  6. FRC CSC RAS, Moscow, Russia

    Igor Pospelov

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Goncharov, E.N. (2022). An Improved Genetic Algorithm for the Resource-Constrained Project Scheduling Problem. In: Olenev, N., Evtushenko, Y., Jaćimović, M., Khachay, M., Malkova, V., Pospelov, I. (eds) Advances in Optimization and Applications. OPTIMA 2022. Communications in Computer and Information Science, vol 1739. Springer, Cham. https://doi.org/10.1007/978-3-031-22990-9_3

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  • DOI: https://doi.org/10.1007/978-3-031-22990-9_3

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