Summary: Evolutionary computation techniques constitute an important category of heuristic search. Any evolutionary algorithm applied to a particular problem must address the issue of genetic representation of solutions to the problem and genetic operators that would alter the genetic composition of offspring during the reproduction process. However, additional heuristics should be incorporated in the algorithm as well; these heuristic rules provide guidelines for evaluating unfeasible and feasible individuals. This paper surveys such heuristics for discrete and continuous domains and discusses their merits and drawbacks.
For the entire collection see [Zbl 0869.00056].