Simulated Annealing Conditions to Generate a New Population in Genetic Algorithm
G.S. Biju, A. K. Anilkumar · Global Journal of Pure and Applied Mathematics · 2017
Genetic algorithms and simulated annealing are two important iterative algorithms widely used in combinatorial optimizations.While genetic algorithm is a probabilistic algorithm inspired in design by evolutionary mechanisms found in biological species, simulated annealing is based on the analogy of the cooling and annealing of metals.Both genetic algorithm and simulated annealing have been used for solving numerous problems from a wide range of application domains and have been found to be very effective and robust throughout, and are even suitable for ill-posed problems where some of the parameters are not known before hand.In this paper we propose simulated annealing based probability conditions to generate a new population in genetic algorithm.The proposed algorithm does not make use of the mutation operation.The new algorithm is validated with standard test cases and the results are compared with genetic algorithm and simulated annealing algorithm.The results obtained indicate a promising performance of the new approach in genetic algorithm.