@ARTICLE{Nezhadhosein, author = {Nezhadhosein, S. and Heydari, A. and Ghanbari, R. and }, title = {Integrating Differential Evolution Algorithm with Modified Hybrid GA for Solving Nonlinear Optimal Control Problems}, volume = {12}, number = {1}, abstract ={‎Here‎, ‎we give a two phases algorithm based on integrating differential evolution (DE) algorithm with modified hybrid genetic algorithm (MHGA) for solving the associated nonlinear programming problem of a nonlinear optimal control problem‎. ‎In the first phase‎, ‎DE starts with a completely random initial population where each individual‎, ‎or solution‎, ‎is a random matrix of control input values in time nodes‎. ‎After phase 1‎, ‎to achieve more accurate solutions‎, ‎we increase the number of time nodes‎. ‎The values of the associated new control inputs are estimated by linear or spline interpolations using the curves computed in the phase 1‎. ‎In addition‎, ‎to maintain the diversity in the population‎, ‎some additional individuals are added randomly‎. ‎Next‎, ‎in the second phase‎, ‎MHGA starts by the new population constructed by the above procedure and tries to improve the obtained solutions at the end of phase 1‎. ‎We implement our proposed algorithm on some well-known nonlinear optimal control problems‎. ‎The numerical results show the proposed algorithm can find almost better solution than other proposed algorithms‎. }, URL = {http://ijmsi.ir/article-1-595-en.html}, eprint = {http://ijmsi.ir/article-1-595-en.pdf}, journal = {Iranian Journal of Mathematical Sciences and Informatics}, doi = {DOI: 10.7508/ijmsi.2017.01.005}, year = {2017} }