approximate pareto optimal solutions of multi-objective optimal control problems by evolutionary algorithms

in this paper an approach based on evolutionary algorithms to find pareto optimal pair of state and control for multi-objective optimal control problems (moocp)'s is introduced‎. ‎in this approach‎, ‎first a discretized form of the time-control space is considered and then‎, ‎a piecewise linear control and a piecewise linear trajectory are obtained from the discretized time-control space using a numerical method‎. ‎to do that‎, ‎a modified version of two famous evolutionary genetic algorithm (ga) and particle swarm optimization (pso) to obtain pareto optimal solutions of the problem is employed‎. ‎numerical examples are presented to show the efficiency of the given approach.