Faculty of Engineering, Okayama University Acta Medica Okayama 0475-0071 30 1 1995 Stability and Sensitivity Analysis in Convex Vector Optimization 121 131 EN Tetsuzo Tanino Masahiro Tanaka In this paper we provide some theoretical results on stability and sensitivity analysis in convex vector optimization. Given a family of parametrized vector optimization problems, the perturbation maps are defined as the set-valued map which associates to each parameter value the set of minimal points (properly minimal points, weakly minimal points) of the perturbed feasible set with respect to an ordering convex cone. Sufficient conditions for the upper and lower semicontinuity of the perturbations map are obtained. We also provide quantitative properties of the perturbation maps under some convexity assumptions. No potential conflict of interest relevant to this article was reported.

Faculty of Engineering, Okayama University Acta Medica Okayama 0475-0071 30 1 1995 Genetic Algorithm with Evolutionary Chain-Based Mutation and Its Applications 111 120 EN Masahiro Tanaka Tetsuzo Tanino Mutation is one of the important operators in genetic algorithm. In traditional genetic algorithm, mutation is activated stochastically. In this way it is unknown and cannot be controlled for which individuals to be mutated. Therefore, it is unavoidable that some good individuals are destroyed by mutation and then the evolutionary efficiency of the genetic algorithm is dampened. Owing to this kind of destructivity of mutation, the operator of mutation has to be limited within a very small probability, and the potentiality of mutation is consequently limited. In this paper, we present an evolutionary chain-based mutation and a control strategy of reasonable competition, in which the heuristic information provided by the evaluation function is well utilized. This method avoids the blindness of stochastic mutation. The performance improved in this method is shown by two examples, a fuzzy modeling for the identification of a nonlinear function and a typical combinatorial optimization problem-the traveling salesman problem. No potential conflict of interest relevant to this article was reported.