کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
570676 | 1446523 | 2016 | 8 صفحه PDF | دانلود رایگان |
In communication networks, we need to find the shortest path frequently. For finding the shortest path there are several methods. Travelling salesman problem (TSP) is also a problem of finding a shortest path. TSP has several applications such as planning, logistics, manufacture of microchips, Flight simulation etc. There are several methods for solving TSP such as dynamic programming, branch and bound method and linear programming.Here we analyze a Meta heuristics swarm intelligent approach to solve TSP approximately. An Ant Colony Optimization (ACO) is a Meta heuristics swarm intelligent optimization technique. An ACO is one of the best methods to find the shortest path. ACO uses parameters called alpha, beta (also called control parameters) and evaporation rate, to find the shortest path on probability basis. We have tried to optimize these parameters to find the path of minimum length and cost.
Journal: Procedia Computer Science - Volume 92, 2016, Pages 48–55