Investigation of ant colony optimization with Levy flight technique for a class of stochastic combinatorial optimization problem

The demand for efficient solutions to optimization problems with uncertain and stochastic data is increasing.  Probabilistic traveling salesman problem (PTSP) is a class of Stochastic Combinatorial Optimization Problems (SCOPs) involving partially unknown information about problem data with a known probability distribution.  It consists to minimize the expected length of the tour where each customer requires a visit only with a given probability, at which customers who do not need a tour are just ignored without further optimization.  Since the PTSP is NP-hard, the usage of metaheuristic me

A new improved simulated annealing for traveling salesman problem

Simulated annealing algorithm is one of the most popular metaheuristics that has been successfully applied to many optimization problems.  The main advantage of SA is its ability to escape from local optima by allowing hill-climbing moves and exploring new solutions at the beginning of the search process.  One of its drawbacks is its slow convergence, requiring high computational time with a good set of parameter values to find a reasonable solution.  In this work, a new improved SA is proposed to solve the well-known travelling salesman problem.  In order to improve SA