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An Improved Farmland Fertility Algorithm with Hyper-Heuristic Approach for Solving Travelling Salesman Problem

Farhad Soleimanian Gharehchopogh1,*, Benyamin Abdollahzadeh1, Bahman Arasteh2
1 Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran
2 Department of Software Engineering, Faculty of Engineering and Natural Science, Istinye University, Istanbul, Turkey
* Corresponding Author: Farhad Soleimanian Gharehchopogh. Email: bonab.farhad@gmail.com

Computer Modeling in Engineering & Sciences https://doi.org/10.32604/cmes.2023.024172

Received 25 May 2022; Accepted 16 August 2022; Published online 15 September 2022

Abstract

Travelling Salesman Problem (TSP) is a discrete hybrid optimization problem considered NP-hard. TSP aims to discover the shortest Hamilton route that visits each city precisely once and then returns to the starting point, making it the shortest route feasible. This paper employed a Farmland Fertility Algorithm (FFA) inspired by agricultural land fertility and a hyper-heuristic technique based on the Modified Choice Function (MCF). The neighborhood search operator can use this strategy to automatically select the best heuristic method for making the best decision. Lin-Kernighan (LK) local search has been incorporated to increase the efficiency and performance of this suggested approach. 71 TSPLIB datasets have been compared with different algorithms to prove the proposed algorithm’s performance and efficiency. Simulation results indicated that the proposed algorithm outperforms comparable methods of average mean computation time, average percentage deviation (PDav), and tour length.

Keywords

Travelling salesman problem; optimization; farmland fertility optimization algorithm; Lin-Kernighan
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