In this work, we study optimistic planning methods to solve some state-constrained optimal control problems in finite horizon. While classical for calculating the value function are generally based on a discretization state space, algorithms have advantage of using adaptive space. These approaches therefore very suitable where dimension variable is low and allow deal with space can be high. Our...

Objectives optimization and constraints satisfaction are two equally important goals to solve constrained many-objective problems (CMaOPs). However, most existing studies for CMaOPs can be classified as feasibility-driven-constrained evolutionary algorithms (CMaOEAs), they always give priority satisfy constraints, while ignoring the maintenance of population diversity dealing with conflicting o...

In view of the shortcomings whale optimization algorithm (WOA), such as slow convergence speed, low accuracy, and easy to fall into local optimum, an improved (IWOA) is proposed. First, standard WOA from three aspects initial population, factor, mutation operation. At same time, Gaussian introduced. Then nonfixed penalty function method used transform constrained problem unconstrained problem. ...