On enhanced intelligent water drops algorithm for travelling salesman problem under uncertain paradigm

Abstract

Travelling salesman problem (TSP) is a well known combinatorial optimization problem which has drawn colossal attention due to its eclectic range of applications. In this article, we have proposed two modified versions of intelligent water drops (IWD) algorithm. The first one is the enhanced IWD (e-IWD) algorithm to solve single objective TSP. In the second modification, e-IWD algorithm has been extended to enhanced multi-objective IWD(e-MIWD) algorithm for solving multi-objective TSP. In order to achieve a better exploration capability in both of the proposed algorithms, the soil and velocity parameters of a randomly selected water drop are updated after every iteration of the algorithm when it traverses all the intermediate vertices for a tour. The proposed algorithms have been compared with some other existing similar algorithms on different benchmark instances of TSPs. Furthermore, we have addressed the TSP for both single and multiple objectives under uncertain environment.