Meta-Heuristic Solution Approaches for Traveling Salesperson Problem
| Autor: | AHMED, Omar Mohammed Ahmed, KAHRAMANLI, Humar |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 1899 |
| Předmět: | |
| Zdroj: | Volume: 6, Issue: 3 21-26 International Journal of Applied Mathematics Electronics and Computers |
| ISSN: | 2147-8228 |
| Popis: | The traveling salesperson problem (TSP) is the NP-hard optimizationproblems which have been widely studied over the past years. TSP creates aHamiltonian cycle where each node is visited once and only once to minimize thetotal traveled distance. TSPs are difficult to be solved using classicalmathematical methods. Even with nowadays computers solving TSP problems withthese methods takes very plenty of time. Therefore, many efficient optimizationmethods have been focused for academic proposes for the TSP all the times. Mostof the TSP problems are now solved by meta-heuristic methods, that provides asatisfactory solutions in real-time. Meta-heuristic algorithms were inspiredfrom behaviors of animals and insects such as ants, bees, fish schools, birdflocks and mammals.This paper focuses on three meta-heuristic methods: WhaleOptimization Algorithm (WOA), Particle Swarm Optimization (PSO) algorithm andGrey Wolf Optimizer (GWO). The problem for application was selected fromTSPLIB. Probably the best implemented solutions were Whale OptimizationAlgorithm and Grey Wolf Optimizer which can be recommended as primary algorithmto solve the TSP or to start with the meta-heuristic solution |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|