علی سعداله

استاديار

گروه مکانیک- دانشکده فنی مهندسی

داخلی : 394

ایمیل: sadollah@usc.ac.ir

اتاق: دفتر معاونت پژوهشی – طبقه سوم ساختمان فرهنگ

Google Scholar: 7344      H-index: 35

سوابق تحصيلات

کارشناسی مهندسی مکانییک – دانشگاه آزاد اسلامی سمنان 1386 -1381

کاشناسی ارشد مهندسی مکانیک گرایش طراحی کاربردی – دانشگاه سمنان   1389-1386

دکتری مهندسی مکانیک – دانشگاه Malayaب  1392-1389

سوابق اجرایی

  • معاون پژوهشی دانشگاه علم و فرهنگ (از سال 1404 تا کنون)
  • سرپرست معاونت پژوهشی دانشگاه علم و فرهنگ (از سال 1403 تا 1404)
  • عضو هیات علمی دانشگاه علم و فرهنگ (از سال 1397 تا کنون)

ﻣﻘﺎﻻت

  • Sadollah, M. Nasir, Z.W. Geem*, “Sustainability and optimization: from conceptual fundamentals to applications”, Sustainability, 12(5) (2020) 2027 (1-34) (IF: 3.251, Q1).
  • Nasir, A. Sadollah, Y.H. Choi, J.H. Kim*, “A comprehensive review on water cycle algorithm and its applications”, Neural Computing and Applications, 32 (2020) 17433-17488 (IF: 5.606, Q1).
  • Nasir, A. Sadollah, J.H. Yoon, Z.W. Geem*, “Comparative study of harmony search algorithm and its applications in China, Japan and Korea” Applied Sciences, 10 (2020) 3970 (1-26) (IF: 2.679, Q2).
  • Yadav*, A. Sadollah, N. Yadav, J.H. Kim, “Self-adaptive global mine blast algorithm for numerical optimization”, Neural Computing and Applications, 32 (2020) 2423-2444 (IF: 5.606, Q1).
  • Gao, Y. Huang, A. Sadollah, L. Wang*, “A review of energy-efficient scheduling in intelligent production systems”, Complex & Intelligent Systems, 6 (2020) 237-249, Complex & Intelligent Systems (IF: 5.8, Q1).
  • Sadollah, “How do artificial neural networks lead to developing an optimization method?” Trends in Computer Science and Information Technology, 5(1) (2020) 67-69. 2022
  • Nasir*, A. Sadollah, I. Berkan Aydilek, A. Lashkar Ara, S.A. Nabavi-Niaki, “A combination of FA and SRPSO algorithm for Combined Heat and Power Economic Dispatch”, Applied Soft Computing, 102 (2021) 107088 (IF: 8.7, Q1).
  • Sadollah, K. Gao, J.H. Kim*, “Memetic computing for imprecise solution of T-shaped heat transfer fins” Engineering Optimization, 53(9) (2021) 1504-1522 (IF: 3.230,Q2).
  • M.H. Almasi, Y. Oh, A. Sadollah, Y.J. Byon, S. Kang*, “Urban transit network optimization under variable demand with single and multi-objective approaches using metaheuristics: The case of Daejeon, Korea”, International Journal of Sustainable Transportation, 15(5) (2021) 1-21 (IF: 3.929, Q1).
  • Nasir, A. Sadollah, P. Grzegorzewski, J.H. Yoon, Z.W. Geem*, “Harmony search algorithm and fuzzy logic theory: an extensive review from theory to applications”,Mathematics, 9 (2021) 2665 (IF: 2.4, Q2).
  • Hou, Y. Fu*, K. Gao, H. Zhang, A. Sadollah, “Modelling and Optimization of Integrated Distributed Flow Shop Scheduling and Distribution Problems with Time Windows”, Expert System with Applications, 187 (2022) 115827 (IF: 6.954, Q1).
  • He, K. Wang, H. Li, H. Song, Z. Lin, K. Gao*, A. Sadollah, “Improved Q-learning algorithm for solving permutation flow shop scheduling problems”, IET Collaborative Intelligent Manufacturing, 4(1) (2022) 35-44 (Scopus Index, Q1).
  • Fu, Y. Hou*, Z. Chen, X. Pu, K. Gao, A. Sadollah, “Modelling and scheduling integration of distributed production and distribution problems via black widow optimization”, Swarm and Evolutionary Computation, 68 (2022) 101015 (IF: 10.267, Q1).
  • S.M. Razavi*, A. Sadollah, A.K. Al-Shamiri, “Prediction and optimization of electrical conductivity for polymer-based composites using design of experiment and artificial neural networks”, Neural Computing and Applications, 34 (2022) 7653-7671 (IF: 5.606, Q1).
  • Ziyaei, M. Khorasanchi*, H. Sayyadi, A. Sadollah, “Minimizing the levelized cost of energy in an offshore wind farm with non-homogeneous turbines through layout optimization”, Ocean Engineering, 249 (2022) 110859 (IF: 3.795, Q1).
  • Etaati*, A. Abdollahi Dehkordi, A. Sadollah, M. El-Abd, M. Neshat, “A comparative state-of-the-art constrained metaheuristics frahttps://www.hindawi.com/journals/mpe/2022/6078986/and sizing”, Mathematical Problems in Engineering, Article ID 6078986, 13 pages (IF: 1.43,Q2).
  • Ma, Y. Fu*, K. Gao*, A. Sadollah, K. Wang, “Integration routing and scheduling for multiple home health care centers using a multi-objective cooperation evolutionary algorithm with stochastic simulation” Swarm and Evolutionary Computation, 75 (2022) 101175 (IF: 10.267, Q1).
  • G.H. Lee, A. Sadollah, S.H. Park, Z.W. Geem*, “HS-Solver: Spreadsheet based harmony search algorithm solver for various optimization problems” SoftwareX, 20 (2022) 101262 (IF: 2.868, Q2).
  • Ma, Y. Fu*, K. Gao, L. Zhu, A. Sadollah, “A Multi-Objective Scheduling and Routing Problem for Home Health Care Services via Brain Storm Optimization”, Complex System Modeling and Simulation, 3(1) (2023) 32-46.
  • Khurana, A. Yadav, A. Sadollah, “A non-dominated sorting based multi-objective neural network algorithm”, MethodX, 10, 102152 (IF: 1.9, Q2).
  • Nasir, A. Sadollah, H. Barati, M. Khodabakhshi, J.H. Kim*, “Generation Rescheduling Based Contingency Constrained Optimal Power Flow Considering Uncertainties Through Stochastic Modeling”, IETE Journal of Research, https://doi.org/10.1080/03772063.2023.2245377, (IF: 1.5, Q3).
  • Jahanshiri, A. Sadollah*, “Multi-objective metaheuristic approach for analyzing static and dynamic behaviors of functionally graded Timoshenko beams”, Mechanics of Advanced Materials and Structures, https://doi.org/10.1080/15376494.2023.2286501,(IF: 2.8, Q2).
  • Etaati, M. Neshat, A. Abdollahi Dehkordi, N. Salami Pargoo, M. El-Abd, A. Sadollah, A.H. Gandomi, “Shape and sizing optimisation of space truss structures using a new cooperative coevolutionary-based algorithm”, Results in Engineering, 21 (2024) 101859 (IF: 5, Q2).
  • Fu, X. Ma, K. Gao’, H. Wang, A. Sadollah, L.Y. Chen, “Multi-Objective Migrating Birds Optimization for Solving Stochastic Home Health Care Routing and Scheduling Problems Considering Caregiver Working Time Constraints” Swarm and Evolutionary Computation, (2024) 101484 (IF: 10, Q1).
  • Liu, K. Gao, D. Li, A. Sadollah, “Ensemble evolutionary algorithms equipped with Q-learning strategy for solving distributed heterogeneous permutation flowshop scheduling problems considering sequence-dependent setup time”, IET Collaborative Intelligent Manufacturing. (2024) e12099 (IF: 8.2, Q1).
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