Constrained solid travelling salesman problem using Adaptive Genetic Algorithm in uncertain environment

摘要

In this paper, an Adaptive Genetic Algorithm (AGA) is developed to solve constrained solid travelling salesman problems (CSTSPs) in crisp, fuzzy and rough environments. In the proposed AGA, we model it with `probabilistic selection' technique and `adaptive crossover' with random mutation. A solid travelling salesman problem (STSP) is a tavelling salesman problem (TSP) in which, at each station, there are a number of conveyances available to travel to another station. The costs and risk/discomfort factors are in the form of crisp, fuzzy and rough in nature. In this paper, CSTSPs are illustrated numerically by some empirical data using this algorithm. In each environment, some sensitivity studies due to different risk/discomfort factors and other system parameters are presented.