An improved farmland fertility algorithm with hyper-heuristic approach for solving travelling salesman problem

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Küçük Resim

Tarih

2022

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

TECH SCIENCE PRESS

Erişim Hakkı

info:eu-repo/semantics/openAccess

Özet

ravelling 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.

Açıklama

Anahtar Kelimeler

Travelling Salesman Problem, Optimization, Farmland Fertility Optimization Algorithm, Lin-Kernighan

Kaynak

CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES

WoS Q Değeri

Q2 - Q3

Scopus Q Değeri

N/A

Cilt

Sayı

Künye

Gharehchopogh, F. S., Abdollahzadeh, B., & Arasteh, B. (2022). An Improved Farmland Fertility Algorithm with Hyper-Heuristic Approach for Solving Travelling Salesman Problem. CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES.