Multi-sexual Genetic Algorithm

another, so that it is not possible to improve on any of the objective functions without deteriorating at least one of the other objective functions. This is known as the concept of Pareto optimality (Rao, 1991). In multiobjective optimization, as opposed to single-objective optimization, there may not exist an unambigous optimal solution (global minimum or global maximum). Characteristic of the multiobjective optimization problems is a very large set of acceptable solutions that are superior to the rest of the solutions in the search space when all objectives are considered. At the same time they are not optimal from the point of any single objective. These solutions are known as Pareto-optimal solutions or nondominated solutions. The rest of the solutions are referred to as dominated solutions. Since none of the solutions in a Pareto-optimal set is absolutely better than any other, any one of them is an acceptable solution. The choice of one particular solution depends on the features of the problem and a number of problem-related factors. In this paper a new method for solving multicriteria optimization problems by Genetic Algorithms is proposed. Standard Genetic Algorithms use a population, where each individual has the same sex (or has no sex) and any two individuals can be crossed over. In the proposed Multisexual Genetic Algorithm (MSGA), individuals have an additional feature, their sex or gender and one individual from each sex is used in the recombination process. In our multicriteria optimization application there are as many sexes as optimization criteria and each individual is evaluated according to the optimization criterion related to its sex. Furthermore, a multi-parent crossover is applied to generate offspring of parents belonging to all different sexes, so the offspring represents intermediate solutions not totally optimal with respect to any single criterion. During the execution of the algorithm the set of nondominated solutions is updated and this set is presented as the output of MSGA at the end.