en Optimal design Optimal design پژوهشي Research This paper presents a Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) for the optimal operation of a complex multipurpose and multi-reservoir system. Firstly, MOEA/D decomposes a multi-objective optimization problem into a number of scalar optimization sub-problems and optimizes them simultaneously. It uses information of its several neighboring sub-problems for optimizing each sub-problem. This simple procedure makes MOEA/D have lower computational complexity compared with non-dominated sorting genetic algorithm II (NSGA-II). The algorithm (MOEA/D) is compared with the Genetic Algorithm (NSGA-II) using a set of common test problems and the real-world Zohre reservoir system in southern Iran. The objectives of the case study include water supply of minimum flow and agriculture demands over a long-term simulation period. Experimental results have demonstrated that MOEA/D can improve system performance to reduce the effect of drought compared with NSGA-II superiority. Therefore, MOEA/D is highly competitive and recommended to solve multi-objective optimization problems for water resources planning and management. multi-objective optimization, decomposition, multi-reservoir 167 187 http://ijoce.iust.ac.ir/browse.php?a_code=A-10-66-61&slc_lang=en&sid=1 I. Ahmadianfar 18003194753284600804 18003194753284600804 Yes A. Adib 18003194753284600805 18003194753284600805 No M. Taghian 18003194753284600806 18003194753284600806 No