A Survey Paper on Smart Path Algorithm for Ant Colony Optimization

Ekta Chauhan

doi:10.37591/ecft.v3i1.612

Abstract

Apart from the tremendous research being executed, ad hoc networks is the huge issue for various researchers. Ad hoc network routing is particularly most challenging issue because of its power energy, dynamic nature and inadequate bandwidth. Someway, techniques which are based on the SI for example algorithms of ACO have presented to be a perfect method for developing algorithms of ad hoc networks routing. ACO routing is an effective routing method based on foraging ants’ behaviour. This mechanism of collective intelligence with the help of the researchers is applied to ad hoc network. ACO is algorithm of meta-heuristic which is inspired from the nature to solve numerous issues of combinatorial optimization, for example TSP. There are numerous versions of the ACO used to solve TSP, for example, max-min ant system, rank based ant system, ant, system of elitist ant algorithm system. For enhanced performance, these approaches can be affected in the parallel architecture like CUDA architecture and GPU. GPU gives fully programmable and highly parallel platform. GPUs which contain numerous processing units with global memory of an off-chip can be used for common resolve parallel computation. This paper presents a literature survey on the several TSP solving applying ACO on GPU.Keywords: ACO, ACS, SI, TSPCite this ArticleEkta Chauhan. A survey paper on smart path algorithm for ant colony optimization. E-Commerce for Future & Trends. 2016; 3(1): 1–9p.