Improved discrete cuckoo search for the resource-constrained project scheduling problem
dc.contributor.author | Bibiks, K | |
dc.contributor.author | Hu, YF | |
dc.contributor.author | Li, JP | |
dc.contributor.author | Pillai, P | |
dc.contributor.author | Smith, A | |
dc.date.accessioned | 2019-07-01T11:56:30Z | |
dc.date.available | 2019-07-01T11:56:30Z | |
dc.date.issued | 2018-05-03 | |
dc.identifier.citation | Bibiks, K., Hu, Y. F., Li, J-P., Pillai, P. and Smith, A. (2018) Improved discrete cuckoo search for the resource-constrained project scheduling problem, Applied Soft Computing, 69, pp. 493-503. | en |
dc.identifier.issn | 1568-4946 | en |
dc.identifier.doi | 10.1016/j.asoc.2018.04.047 | en |
dc.identifier.uri | http://hdl.handle.net/2436/622496 | |
dc.description.abstract | © 2018 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. | en |
dc.description.sponsorship | This work is partially funded by the Innovate UK project HARNET – Harmonised Antennas, Radios and Networks under contract no. 100004607. | en |
dc.format | application/PDF | en |
dc.language | en | |
dc.language.iso | en | en |
dc.publisher | Elsevier BV | en |
dc.relation.url | https://www.sciencedirect.com/science/article/pii/S1568494618302382?via%3Dihub | en |
dc.subject | scheduling | en |
dc.subject | resource-constrained project scheduling problem | en |
dc.subject | cuckoo search | en |
dc.subject | metaheuristics | en |
dc.subject | combinatorial optimisation | en |
dc.title | Improved discrete cuckoo search for the resource-constrained project scheduling problem | en |
dc.type | Journal article | en |
dc.identifier.journal | Applied Soft Computing | en |
dc.date.updated | 2019-06-20T17:23:51Z | |
dc.date.accepted | 2018-04-24 | |
rioxxterms.funder | University of Wolverhampton | en |
rioxxterms.identifier.project | UOW010719PP | en |
rioxxterms.version | AM | en |
rioxxterms.licenseref.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | en |
rioxxterms.licenseref.startdate | 2019-05-03 | en |
dc.source.volume | 69 | |
dc.source.beginpage | 493 | |
dc.source.endpage | 503 | |
dc.description.version | Published version | |
refterms.dateFCD | 2019-07-01T11:55:00Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2019-05-03T00:00:00Z |