Title: An improved discreet Jaya optimisation algorithm with mutation operator and opposition-based learning to solve the 0-1 knapsack problem

Authors: Mohammad Subhi Al-Batah; Mohammed Riyad Al-Eiadeh

Addresses: Department of Computer Science, Faculty of Science and Information Technology, Jadara University, Irbid, Jordan ' Department of Computer Science, Faculty of Computer Science and Information Technology, University of Yarmouk, Irbid, Jordan

Abstract: The 0-1 knapsack problem, a prevalent combinatorial optimisation problem, aims to maximise the benefits of a chosen subset of items while ensuring the total capacity is not exceeded. This paper proposes an improved discreet Jaya (IDJaya) algorithm to solve 0-1 knapsack problems. IDJaya includes opposition-based learning (OBL), Jaya algorithm, transfer functions, mutation operator, repair method, and fitness function. OBL is used to improve the diversity of the initial population, while the mutation operator is used to enhance the search capabilities to bypass local optima issues. Transfer functions are used to convert the Jaya algorithm from a continuous to a binary version. The repair method is used to handle infeasible solutions, and the fitness function is used to assess each solution. IDJaya's performance had been tested on a range of benchmark knapsack problems, demonstrating that IDJaya could be an effective alternative solution for various 0-1 knapsack problems.

Keywords: 0-1 knapsack problem; discreet Jaya algorithm; mutation operator; opposition-based learning; OBL; transfer functions; binary optimisation problem.

DOI: 10.1504/IJMOR.2023.134491

International Journal of Mathematics in Operational Research, 2023 Vol.26 No.2, pp.143 - 169

Received: 10 May 2022
Accepted: 09 Jul 2022

Published online: 24 Oct 2023 *

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