Nature-inspired optimization algorithms in knapsack problem: A review

Section: Article
Published
Dec 1, 2019
Pages
55-72

Abstract

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.

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How to Cite

Tawfeeq Basheer, G., & Yahya Algamal, Z. (2019). Nature-inspired optimization algorithms in knapsack problem: A review. IRAQI JOURNAL OF STATISTICAL SCIENCES, 16(3), 55–72. https://doi.org/10.33899/iqjoss.2019.0164174