Nature-inspired optimization algorithms in knapsack problem: A review

Meta-heuristic algorithms have become an arising field of research in recent years. Some of these algorithms have proved to be efficient in solving combinatorial optimization problems, particularly knapsack problem. In this paper, four meta-heuristic algorithms are presented particle swarm optimizat...

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Bibliographic Details
Published in:	المجلة العراقية للعلوم الاحصائية Vol. 16; no. 3; pp. 55 - 72
Main Authors:	Ghalya Tawfeeq Basheer, Zakariya Algamal
Format:	Journal Article
Language:	English
Published:	College of Computer Science and Mathematics, University of Mosul 01-12-2019
Subjects:	0-1 knapsack problem combinatorial optimization problem meta-heuristic algorithms np-hard problem
Online Access:	Get full text
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Summary:	Meta-heuristic algorithms have become an arising field of research in recent years. Some of these algorithms have proved to be efficient in solving combinatorial optimization problems, particularly knapsack problem. In this paper, four meta-heuristic algorithms are presented particle swarm optimization, firefly algorithm, flower pollination algorithm and monarch butterfly optimization in solving knapsack problem as example of NP-hard combinational optimization problems. Based on twenty 0-1 knapsack problem instances, the computational results demonstrated that the binary flower pollination algorithm has the ability to find the best solutions in reasonable time.
ISSN:	1680-855X 2664-2956
DOI:	10.33899/iqjoss.2019.164174