期刊名称：International Review of Management and Marketing
电子版ISSN：2146-4405
出版年度：2016
卷号：6
期号：8S
页码：63-66
语种：English
出版社：EconJournals
摘要：The water flow-like algorithm (WFA) is a relatively new metaheuristic algorithm, which has shown good solution for the Travelling Salesman Problem (TSP) and is comparable to state of the art results. There are various factor influence the performance of WFA for TSP. However, initial solution has also influence the performance of the algorithm. The basic of WFA uses a random searching method for initialization technique. Previous WFA-TSP used Nearest Neighbor for initial solution. Therefore this paper presents the performance of use Simulated Annealing in initial solution for WFA-TSP. The algorithms are evaluated using 16 benchmarks TSP datasets. The experimental results show that the proposed SA-WFA-TSP outperforms due to its capacity of reduce computing time compared with others algorithms especially for large dataset. Therefore, it can be concluded that SA-WFA-TSP has become the state of the art algorithm for TSP. Keywords: Nature-inspired Metaheuristics, Water Flow Liked Algorithm, Simulated Annealing Algorithm, Combinatorial Optimization, Traveling Salesman Problem JEL Classifications: C22, C61
其他摘要：The water flow-like algorithm (WFA) is a relatively new metaheuristic algorithm, which has shown good solution for the Travelling Salesman Problem (TSP) and is comparable to state of the art results. There are various factor influence the performance of WFA for TSP. However, initial solution has also influence the performance of the algorithm. The basic of WFA uses a random searching method for initialization technique. Previous WFA-TSP used Nearest Neighbor for initial solution. Therefore this paper presents the performance of use Simulated Annealing in initial solution for WFA-TSP. The algorithms are evaluated using 16 benchmarks TSP datasets. The experimental results show that the proposed SA-WFA-TSP outperforms due to its capacity of reduce computing time compared with others algorithms especially for large dataset. Therefore, it can be concluded that SA-WFA-TSP has become the state of the art algorithm for TSP. Keywords: Nature-inspired Metaheuristics, Water Flow Liked Algorithm, Simulated Annealing Algorithm, Combinatorial Optimization, Traveling Salesman Problem JEL Classifications: C22, C61
