A Hybrid of Evolutionary Search and Local Heuristic Search for Combinatorial Optimization Problems

Evolutionary algorithms(EAs) have been successfully applied to many combinatorial optimization problems of various engineering fields. Recently, some comparative studies of EAs with other stochastic search algorithms have, however, shown that they are similar to, or even are not comparable to other heuristic search. In this paper, a new hybrid evolutionary algorithm utilizing a new local heuristic search, for combinatorial optimization problems, is presented. The new intelligent local heuristic search is described, and the behavior of the hybrid search algorithm is investigated on two well-known problems: traveling salesman problems (TSPs), and quadratic assignment problems(QAPs). The results indicate that the proposed hybrid is able to produce solutions of high quality compared with some of evolutionary and simulated annealing.