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Naslov:An improved harmony search algorithm using opposition-based learning and local search for solving the maximal covering location problem
Avtorji:ID Atta, Soumen (Avtor)
Datoteke:.pdf An_improved_harmony_search_algorithm_using_opposition-based_learning_and_local_search_for_solving_the_maximal_covering_location_problem.pdf (2,69 MB)
MD5: CD9A2F7DF64168F8257DD1529CBFE93F
 
URL https://www.tandfonline.com/doi/pdf/10.1080/0305215X.2023.2244907
 
Jezik:Angleški jezik
Vrsta gradiva:Neznano
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:UNG - Univerza v Novi Gorici
Opis:In this article, an improved harmony search algorithm (IHSA) that utilizes opposition-based learning is presented for solving the maximal covering location problem (MCLP). The MCLP is a well-known facility location problem where a fixed number of facilities are opened at a given potential set of facility locations such that the sum of the demands of customers covered by the open facilities is maximized. Here, the performance of the harmony search algorithm (HSA) is improved by incorporating opposition-based learning that utilizes opposite, quasi-opposite and quasi-reflected numbers. Moreover, a local search heuristic is used to improve the performance of the HSA further. The proposed IHSA is employed to solve 83 real-world MCLP instances. The performance of the IHSA is compared with a Lagrangean/surrogate relaxation-based heuristic, a customized genetic algorithm with local refinement, and an improved chemical reaction optimization-based algorithm. The proposed IHSA is found to perform well in solving the MCLP instances.
Ključne besede:maximal covering location problem, harmony search algorithm, opposition-based learning, facility location problem, opposite number
Datum objave:01.01.2023
Leto izida:2023
Št. strani:str. 1-20
Številčenje:Vol. , [article no.] ǂ
PID:20.500.12556/RUNG-8546-11e41eec-9e85-76ad-e540-841f0c573101 Novo okno
ISSN:0305-215X
COBISS.SI-ID:167173635 Novo okno
UDK:62
ISSN pri članku:0305-215X
eISSN:1029-0273
DOI:10.1080/0305215X.2023.2244907 Novo okno
NUK URN:URN:SI:UNG:REP:L95WADDN
Datum objave v RUNG:05.10.2023
Število ogledov:1184
Število prenosov:7
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
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Gradivo je del revije

Naslov:Engineering optimization
Skrajšan naslov:Eng. optim.
Založnik:Gordon and Breach.
ISSN:0305-215X
COBISS.SI-ID:10292229 Novo okno

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Licenca:CC BY-NC-ND 4.0, Creative Commons Priznanje avtorstva-Nekomercialno-Brez predelav 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by-nc-nd/4.0/deed.sl
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