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    Improved discrete cuckoo search for the resource-constrained project scheduling problem

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    Hu_et_al_Applied_Soft_Computing.pdf (736.4Kb)
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    Publication date
    2018-08
    Author
    Bibiks, Kirils
    Hu, Yim Fun
    Li, Jian-Ping
    Pillai, Prashant
    Smith, A.
    Keyword
    Scheduling
    Resource-constrained project scheduling problem
    Cuckoo search
    Metaheuristics
    Combinatorial optimisation
    Rights
    Crown Copyright © 2018 Published by Elsevier B.V. All rights reserved. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    An Improved Discrete Cuckoo Search (IDCS) is proposed in this paper to solve resource-constrained project scheduling problems (RCPSPs). The original Cuckoo Search (CS) was inspired by the breeding behaviour of some cuckoo species and was designed specifically for application in continuous optimisation problems, in which the algorithm had been demonstrated to be effective. The proposed IDCS aims to improve the original CS for solving discrete scheduling problems by reinterpreting its key elements: solution representation scheme, Lévy flight and solution improvement operators. An event list solution representation scheme has been used to present projects and a novel event movement and an event recombination operator has been developed to ensure better quality of received results and improve the efficiency of the algorithm. Numerical results have demonstrated that the proposed IDCS can achieve a competitive level of performance compared to other state-of-the-art metaheuristics in solving a set of benchmark instances from a well-known PSPLIB library, especially in solving complex benchmark instances.
    URI
    http://hdl.handle.net/10454/16905
    Version
    Accepted manuscript
    Citation
    Bibiks K, Hu YF, Li J-P et al (2018) Improved discrete cuckoo search for the resource-constrained project scheduling problem. Applied Soft Computing. 69: 493-503.
    Link to publisher’s version
    https://doi.org/10.1016/j.asoc.2018.04.047
    Type
    Article
    Collections
    Engineering and Informatics Publications

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