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