Damghan University Press Analytical and Numerical Solutions for Nonlinear Equations 3060-785X 4 1 2019 12 01 Pareto-optimal Solutions for Multi-objective Optimal Control Problems using Hybrid IWO/PSO Algorithm جوابهای بهینه پارتو برای مسایل کنترل بهینه چندهدفه با استفاده از الگوریتم تلفیقی علف هرز و تجمع ذرات 41 60 157 10.22128/gadm.2019.300.1021 EN Gholam Hosein Askari Robati Department of Mathematics, Payame Noor University, P.O.Box 19395-3697, Tehran, Iran Akbar Hashemi Borzabadi School of Mathematics and Computer Science, Damghan University, Damghan, Iran Aghileh Heydari Department of Mathematics, Payame Noor University, Tehran, Iran Journal Article 2019 03 31 Heuristic optimization provides a robust and efficient approach for<br />extracting approximate solutions of multi-objective problems because of their<br />capability to evolve a set of non-dominated solutions distributed along the<br />Pareto frontier. The convergence rate and suitable diversity of solutions are<br />of great importance for multi-objective evolutionary algorithms. The focus of<br />this paper is on a hybrid method combining two heuristic optimization techniques, Invasive Weed Optimization (IWO) and Particle Swarm Optimization<br />(PSO), to find approximate solutions for multi-objective optimal control problems (MOCPs). In the proposed method, the process of dispersal has been<br />modified in the MOIWO. This modification will increase the exploration power<br />of the weeds and reduces the search space gradually during the iteration process. Thus, the convergence rate and diversity of solutions along the Pareto<br />frontier have been promote. Finally, the ability of the proposed algorithm is<br />evaluated and compared with conventional NSGA-II and NSIWO algorithms<br />using three practical MOCPs. The results show that the proposed algorithm<br />has better performance than others in terms of computing time, convergence<br />and diversity. https://ansne.du.ac.ir/article_157_a58d415319be498fdbd8c6f7ace604b0.pdf