Solving Multi-Objective Resource Allocation Problem Using Multi-Objective Binary Artificial Bee Colony Algorithm

Resource allocation is the optimal distribution in a limited number of resources available for certain activities. The allocation of the resources for a large number of activities requires exponentially multiplying a computation cost. Therefore, the resource allocation problem is known as NP-Hard pr...

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Vydané v:Arabian journal for science and engineering (2011) Ročník 46; číslo 9; s. 8535 - 8547
Hlavní autori: Yilmaz Acar, Zuleyha, Başçiftçi, Fatih
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2021
Springer Nature B.V
Predmet:
Engineering
Humanities and Social Sciences
multidisciplinary
Optimization algorithms
Research Article-Computer Engineering and Computer Science
Resource allocation
Science
Search algorithms
Swarm intelligence
Transfer functions
Artificial Bee Colony Algorithm
Multi-objective Optimization
Transfer Functions
Multi-objective Resource Allocation Problem
Binary Optimization
ISSN:2193-567X, 1319-8025, 2191-4281
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Shrnutí:Resource allocation is the optimal distribution in a limited number of resources available for certain activities. The allocation of the resources for a large number of activities requires exponentially multiplying a computation cost. Therefore, the resource allocation problem is known as NP-Hard problem in the literature. In this study, a multi-objective binary artificial bee colony algorithm has been proposed for solving the multi-objective resource allocation problems. The proposed algorithm has benefited from the robust structure and easy implementation properties of the artificial bee colony algorithm. The contribution is to introduce the multi-objective version of the artificial bee colony algorithm with advanced local search and binary format using transfer functions. The multi-objective binary artificial bee colony algorithm has been improved as two versions using sigmoid and hyperbolic tangent transfer functions to be able to search in the binary search space. With the proposed algorithms, the multi-objective resource allocation problems in the literature are solved, and the algorithms are compared with other algorithms that develop for the same problems. The results obtained show that the proposed algorithms give effective results on the problem. Especially, in large-scale problems, higher accuracy values are reached with a smaller number of evaluations.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:2193-567X
1319-8025
2191-4281
DOI:10.1007/s13369-021-05521-x