Intelligent Optimization of Complex Energy Systems for Sustainable Logistics and Supply Chain Management

Intelligent Optimization of Complex Energy Systems for Sustainable Logistics and Supply Chain Management

The limitations of energy resources and the increasing consumption of energy on the one hand, and the wasteful use of energy by different societies on the other hand, have resulted in the growing need for the development of efficient energy systems. The implementation of such systems is crucial in reducing environmental pollution and minimizing the waste of national capital. Since the last decade, strict sustainability regulations have been laid down on individual companies and supply chains operating in both the manufacturing and service sectors. To comply with these regulations and meet the increasing demand for sustainable issues, it has become essential for business firms to utilize efficient energy systems to gain a competitive advantage in today's competitive market while also contributing to a more sustainable future.

Given the dynamic and complex nature of energy systems in logistics and supply chain management with numerous decision variables such as material and production planning, packaging, transportation, warehousing, and inventory management, traditional optimization methods may not suffice. With the continued complexity of energy systems, there has been an increasing interest in developing intelligent optimization techniques to plan more efficient energy management systems. These methods rely on artificial intelligence, machine learning, fuzzy systems, optimization algorithms, and other soft computing tools to improve the efficiency of energy management strategies and achieve greater sustainability. By adopting intelligent optimization techniques, supply chain managers can make informed decisions to optimize energy usage, reduce economic costs, and minimize environmental impacts, while achieving strategic business priorities and profitability objectives.

This special issue aims to explore the latest advancements in intelligent optimization for tackling complex issues associated with energy management systems in sustainable logistics and supply chains. We welcome experts from both academia and industry to submit their research and survey papers of superior quality that address the following potential topics, but not limited to:

  • Multi-objective optimization techniques for energy systems design and management

  • Machine learning and deep learning for energy consumption forecasting

  • Knowledge-based fuzzy control systems for energy management

  • Simulation-based optimization methods for resilient energy systems

  • Optimization of complex energy systems with multiple energy storage systems

  • Optimization of multiple renewable energy systems such as wind and solar energy

  • Optimization of energy conversion technologies for supply chain management

  • Optimization of energy distribution networks in supply chain management

  • Heuristic and hype-heuristic algorithms for just-in-time energy control systems

  • Life cycle assessment of energy consumption in supply chain management

  • Energy-efficient routing and scheduling of transportation systems

  • Energy-aware optimization of packaging and materials handling

  • Robust optimization for nonlinear dynamic time-dependent energy systems

  • Stochastic programming and stochastic optimal control in complex energy systems

  • Applications of game theory, rough sets theory, and grey theory in complex energy systems

  • Intelligent optimization with explicit risk measures under uncertainty

  • Approximate solution methods based on interval analysis theory under uncertainty

  • Review state-of-arts in the intersection of intelligent optimization methods and energy systems

Important Dates:

Submission Open: October 1, 2023

Submission Deadline: October 30, 2024

First Decision: Maximum 3 months after submission

Final Decision: Maximum 6 months after submission

Guest Editors:

Dr. Alireza Goli

Department of Industrial Engineering, University of Isfahan, Iran. Email:

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Alireza Goli is currently an assistant professor at the University of Isfahan, Iran. He received his Ph.D. degree in Industrial Engineering from Yazd University, Yazd, Iran, in 2019. He has published more than 60 papers in high-quality journals and conferences. He has been recognized as one of the top 2% of Researchers/Scientists in 2021, identified by Elsevier BV, Stanford University. He is serving as a reviewer in journals such as Expert Systems with Applications, Journal of Supercomputing, IEEE Transactions on Fuzzy Systems, and Annals of Operations Research. He has been working as a Guest Editor in some reputable journals like Development and Sustainability, Environmental Science and Pollution Research, and Environment. He is working as a member of the editorial board of Mathematical Problems in Engineering and Journal of Applied Research in Industrial Engineering. His research interests include logistics and supply chain management, circular economy, heuristic and meta-heuristic algorithms, robust optimization, and artificial intelligence.

Dr. Erfan Babaee Tirkolaee

Department of Industrial Engineering, Istinye University, Istanbul, Turkey. Email:

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Erfan Babaee Tirkolaee obtained a BSc. (2012) and MSc. (2014) in Industrial Engineering from Isfahan University of Technology in Isfahan, Iran. Then, he received a Ph.D. degree (2019) in Industrial Engineering from Mazandaran University of Science and Technology in Babol, Iran. He is currently an assistant professor in the Department of Industrial Engineering at Istinye University in Istanbul, Turkey. Meanwhile, he worked as a Quality Assurance consultant and Training manager in some automotive industries in Iran, and could go through different relevant courses like ISO 9001: 2015 and IATF 16949-2016. He has been verified as a scientific elite by the Young Researchers and Elite Club in 2017 and Iran's National Elites Foundation in 2018. He has published more than 80 papers in high-quality journals, including IEEE Transactions on Fuzzy Systems, Expert Systems with Applications, Waste Management, Journal of Cleaner Production, Computers & Industrial Engineering, Annals of Operations Research, etc. His eleven papers have been selected as ESI Highly Cited Papers. He has been serving as a chair/organizing&committe member/keynote speaker in several prestigious international conferences, and as a reviewer in many reputed WoS journals such that he has been recognized as a Top Peer Reviewer in 2 of the Essential Science Indicators research areas by Clarivate WoS. He is currently an Associate Editor of Expert Systems with Application (Elsevier) and an Editorial Advisory Board member of Management Decision (Emerald). Moreover, he has been serving on the guest editorial board in several journals such as Annals of Operations Research (Springer) and Environmental Science and Pollution Research (Springer). Recently, he has been featured among the "World’s Top 2% Researchers/Scientists in 2021" list identified by Elsevier BV, Stanford University. His research fields include Waste Management, Supply Chain Management, Solution Algorithms, Industrial Engineering, Operations Research, Fuzzy Programming, and Robust Optimization.

Dr. Mohammad Shokouhifar

Department of Electrical and Computer Engineering, Shahid Beheshti University, Tehran, Iran. Email:

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Mohammad Shokouhifar received an MSc. degree in Artificial Intelligence from the Islamic Azad University, Central Tehran Branch, Tehran, Iran, in 2011. He received another MSc. and Ph.D. from the Electrical & Computer Engineering Department at Shahid Beheshti University, Tehran, Iran, in 2013 and 2017, respectively. He has been serving as a reviewer in prestigious journals such as Omega, Expert Systems with Applications, Engineering Applications of Artificial Intelligence, Applied Soft Computing, Computer Networks, Computer Communications, Biomedical Signal Processing and Control, IEEE Access, IEEE Transactions on Fuzzy Systems, IET – Communications, IET – Wireless Sensor Networks, Sustainability, Logistics, Sensors, Electronics, and Mathematics. His research interests include optimization, meta-heuristics, fuzzy sets and systems, knowledge-based heuristic and hyper-heuristic algorithms, energy and exergy optimization systems, hybrid algorithm design, machine learning, deep learning, control systems, manufacturing systems, industrial engineering, and just-in-time scheduling, logistics, and supply chain management.

Prof. Dr. Gerhard-Wilhelm Weber

Faculty of Engineering Management, Poznan University of Technology, Poland. Email:

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Gerhard-Wilhelm Weber is a Professor at Poznan University of Technology, Poznan, Poland, at the Faculty of Engineering Management. His research is on mathematics, operational research, finance, economics, optimization and control, natural, neuro-, bio-, and earth-sciences, medicine, data science, artificial intelligence, and cosmology. He is involved in the organization of scientific life internationally. He received Diploma and Doctorate in Mathematics and Economics/Business Administration, at RWTH Aachen, and Habilitation at TU Darmstadt (Germany). He replaced Professorships at the University of Cologne, and TU Chemnitz, Germany. At the Institute of Applied Mathematics, Middle East Technical University, Ankara, Turkey, he was a Professor in both Financial Mathematics and Scientific Computing, and Assistant to the Director, and has been a member of five further graduate schools, institutes, and departments of METU. He has different affiliations at the Universities of Siegen (Germany), Federation University (Ballarat, Australia), University of Aveiro (Portugal), University of North Sumatra (Medan, Indonesia), Malaysia University of Technology, Chinese University of Hong Kong, KTO Karatay University (Konya, Turkey), Mazandaran University of Science and Technology (Babol, Iran) and Georgian International Academy of Science, at EURO (Association of European OR Societies) where he is “Advisor to EURO Conferences” and IFORS Fellow; he is a member in many national OR societies and working groups, at Pacific Optimization Research Activity Group, etc. He has (co-) supervised many MSc. and Ph.D. students, (co-) authored numerous books, special issues, and articles, and given many presentations from a diversity of subject areas, on theory, methods, and practice. He has been a member of many international editorial and award boards; he participated in and was in charge of numerous research projects; he received various recognitions and awards from students, universities, conferences, and scientific organizations.