Solution of Fuzzy Dynamic Optimization Problems by Adaptive Stochastic Algorithm

This article proposes a novel algorithm for optimizing a nonlinear dynamic system subjected to flexible path constraints. Each flexible constraint is fuzzified by using the concept of degree-of-acceptability, and the fuzzy degree-of-satisfaction for the objective is then derived. The numerical method of Integrated Controlled Random Search for Dynamic System (ICRS/DS) is applied here for solving the resulting fuzzy decision problem. One numerical example is supplied, demonstrating the applicability of the proposed algorithm.