TY - JOUR ID - 3394 TI - Compression of novel meta-heuristic algorithms for multi-objective optimization of water resources system (case study: Sistan’s Chah Nimeh) JO - Amirkabir Journal of Civil Engineering JA - CEEJ LA - en SN - 2588-297X AU - Akbarpour, Abolfazl AU - Mohsen Pourreza Bilondi, mohsen AU - zeynali, mohammad javad AD - Faculty of Engineering, University of Birjand AD - university of birjand AD - Ph. D. Student, Dep. of Sciences and Water Engineering, Birjand University, Iran. Y1 - 2020 PY - 2020 VL - 52 IS - 8 SP - 2011 EP - 2024 KW - Antlion Algorithm KW - Grasshopper Algorithm KW - Particle swarm algorithm KW - Performance Ceriteria DO - 10.22060/ceej.2019.15818.6039 N2 - In this research, two conflicting objective functions used to solve the problem of optimization operation of Sistan’s Chah Nimeh reservoirs. The first objective function defined minimizing the total of second power of difference between agricultural demand and release and the second objective function defined maximizing the reliability index. In this study, to compare the studied algorithms, the criteria of the algorithm’s run time, the number of solutions in the optimal Pareto front, and distance, dispersion, convergence and generation distance were taken. The results of the study of Meta-Heuristic algorithms indicated that among MOPSO, MOGOA and MOALO algorithms, MOALO and MOGOA algorithms were more efficient than MOPSO algorithm. According to the performance criteria of the algorithm’s run time and the dispersion criteria, the MOPSO algorithm showed high efficiency and according to the performance criteria of the distance, convergence and generation distance criteria, the MOGOA showed high efficiency. According to the performance criteria of the number of solutions on the optimal Pareto front MOALO algorithm showed high efficiency. Also, MOALO and MOGOA algorithms effectively covered optimal pareto front. It can be said, the solutions of these algorithms find in themselves optimal pareto front, create a rich set of optimal solutions that not only effectively cover the optimal Pareto front, but also dominate the solutions of the other two algorithms. Therefore, it seems that none of these performance criteria can alone determine the superiority of an algorithm than other algorithms in solving an optimization problem. UR - https://ceej.aut.ac.ir/article_3394.html L1 - https://ceej.aut.ac.ir/article_3394_dded6a2c6ebc5e0cc5f72f5246eb88c7.pdf ER -