Povzetek

The Uncapacitated Facility Location Problem (UFLP) is considered in this paper. Given a set of customers and a set of potential facility locations, the objective of UFLP is to open a subset of facilities to satisfy the demands of all the customers such that the sum of the opening cost for the opened facilities and the service cost is minimized. UFLP is a well-known combinatorial optimization problem which is also NP-hard. So, a metaheuristic algorithm for solving this problem is natural choice. In this paper, a relatively new swarm intelligence-based algorithm known as the Monkey Algorithm (MA) is applied to solve UFLP. To validate the efficiency of the proposed binary MA-based algorithm, experiments are carried out with various data instances of UFLP taken from the OR-Library and the results are compared with those of the Firefly Algorithm (FA) and the Artificial Bee Colony (ABC) algorithm.

Ključne besede

uncapacitated facility location problem;simple plant location problem;warehouse location problem;monkey algorithm;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.08 - Objavljeni znanstveni prispevek na konferenci
Organizacija: UNG - Univerza v Novi Gorici
UDK: 004
COBISS: 149331459 Povezava se bo odprla v novem oknu
Št. ogledov: 131
Št. prenosov: 0
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

URN: URN:SI:UNG
Vrsta dela (COBISS): Delo ni kategorizirano
Strani: Str. 71-78
DOI: 10.1007/978-981-10-7566-7_8
ID: 18625136