Genetic Algorithms (GA), Simulated Annealing (SA), Differential Evolution (DE), Self Organising Migrating Algorithms (SOMA), Travelling Salesman Problem (TSP).

Evolutionary algorithms are general iterative algorithms for combinatorial optimization. The term evolutionary algorithm is used to refer to any probabilistic algorithm whose design is inspired by evolutionary mechanisms found in biological species. These algorithms have been found to be very effective and robust in solving numerous problems from a wide range of application domains. In this paper we perform a comparative study among Genetic Algorithms (GA), Simulated Annealing (SA), Differential Evolution (DE), and Self Organising Migrating Algorithms (SOMA). These algorithms have many similarities, but they also possess distinctive features, mainly in their strategies for searching the solution state space. The four heuristics are applied on the same optimization problem - Travelling Salesman Problem (TSP) and compared with respect to (1) quality of the best solution identi?ed by each heuristic, (2) progress of the search from an initial solution until stopping criteria are met.