High-level hybridization of heuristics and metaheuristics to solve symmetric TSP: a comparative study
Carlos Alberto da Silva Junior, Roberto Yuji Tanaka, Luiz Carlos, Farias da Silva, Angelo Passaro

TL;DR
This study evaluates high-level hybridizations of eight metaheuristics with heuristics for solving the symmetric TSP, comparing their effectiveness without parameter tuning across problems with 50 to 280 cities.
Contribution
It provides a comparative analysis of various hybrid metaheuristic-heuristic combinations for symmetric TSP, highlighting the impact of different search mechanisms.
Findings
Certain hybrid combinations outperform existing solutions.
Metaheuristic search patterns significantly influence solution quality.
Parameter tuning is unnecessary due to inherent search pattern diversity.
Abstract
The Travelling Salesman Problem - TSP is one of the most explored problems in the scientific literature to solve real problems regarding the economy, transportation, and logistics, to cite a few cases. Adapting TSP to solve different problems has originated several variants of the optimization problem with more complex objectives and different restrictions. Metaheuristics have been used to solve the problem in polynomial time. Several studies have tried hybridising metaheuristics with specialised heuristics to improve the quality of the solutions. However, we have found no study to evaluate whether the searching mechanism of a particular metaheuristic is more adequate for exploring hybridization. This paper focuses on the solution of the classical TSP using high-level hybridisations, experimenting with eight metaheuristics and heuristics derived from k-OPT, SISR, and segment…
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Taxonomy
TopicsVehicle Routing Optimization Methods
MethodsSparse Evolutionary Training
