A bi-objective model of the energy allocation problem is established. A multi-objective evolutionary algorithm is proposed to solve it. The proposed MOEA uses set-based p...
Abstract:
In this paper, the energy allocation problem of major production equipment is investigated from the perspective of the whole production process to meet the energy demands...Show MoreMetadata
Abstract:
In this paper, the energy allocation problem of major production equipment is investigated from the perspective of the whole production process to meet the energy demands of the production system in the iron and steel enterprise. Taking into account the replacement between energy and the changeover state of equipment, a bi-objective mixed integer programming model is established to minimize the total energy cost and changeover cost of equipment. A multi-objective evolutionary algorithm (MOEA) is proposed to solve the model. The MOEA takes into account the correlation among variables in the model and extracts free variables to encode the individual. In order to preserve and utilize the local non-dominated information during evolution, a set-based population structure is proposed. A self-adaptive selection strategy of crossover operators is also designed to improve the efficiency of evolution. With the aid of the 0-1 state variables in the model, an improvement and updating mechanism is proposed to improve the quality and diversity of the external archive, which can help to prevent the evolution from premature or trapping in a local optimum. The computational results based on 160 practical instances illustrate that the proposed MOEA is superior to NSGA-II and MOEA/D and has potential application ability in practical production.
A bi-objective model of the energy allocation problem is established. A multi-objective evolutionary algorithm is proposed to solve it. The proposed MOEA uses set-based p...
Published in: IEEE Access ( Volume: 7)
Funding Agency:
Key Laboratory of Data Analytics and Optimization for Smart Industry, Ministry of Education, Liaoning Engineering Laboratory of Operation Analytics and Optimization for Smart Industry, Northeastern University, Shenyang, China
Linlin Li received the B.Sc. degree in computer and application and the M.Sc. degree in computer application technology from Northeastern University, Shenyang, China, in 2002 and 2005, respectively, where she is currently pursuing the Ph.D. degree in system engineering with the College of Information Science and Engineering.
She is also an Associate Professor with the School of Software, University of Science and Technolog...Show More
Linlin Li received the B.Sc. degree in computer and application and the M.Sc. degree in computer application technology from Northeastern University, Shenyang, China, in 2002 and 2005, respectively, where she is currently pursuing the Ph.D. degree in system engineering with the College of Information Science and Engineering.
She is also an Associate Professor with the School of Software, University of Science and Technolog...View more
Key Laboratory of Data Analytics and Optimization for Smart Industry, Ministry of Education, Liaoning Engineering Laboratory of Operation Analytics and Optimization for Smart Industry, Northeastern University, Shenyang, China
Zan Wang received the B.S. degree in industrial engineering from Northeastern University, Shenyang, China, in 2015, where he is currently pursuing the master’s degree with the Liaoning Engineering Laboratory of Operations Analytics and Optimization for Smart Industry. His current research interests include multi-factor optimization, machine learning, and their applications.
Zan Wang received the B.S. degree in industrial engineering from Northeastern University, Shenyang, China, in 2015, where he is currently pursuing the master’s degree with the Liaoning Engineering Laboratory of Operations Analytics and Optimization for Smart Industry. His current research interests include multi-factor optimization, machine learning, and their applications.View more
Liaoning Key Laboratory of Manufacturing System and Logistics, Institute of Industrial and Systems Engineering, Northeastern University, Shenyang, China
Xianpeng Wang (M’ 11) received the B.S. degree in materials and control engineering from Shenyang University, Shenyang, China, and the Ph.D. degree in systems engineering from Northeastern University, Shenyang, in 2002 and 2007, respectively, where he is currently a Professor with the Liaoning Engineering Laboratory of Operations Analytics and Optimization for Smart Industry and the State Key Laboratory of Synthetical Aut...Show More
Xianpeng Wang (M’ 11) received the B.S. degree in materials and control engineering from Shenyang University, Shenyang, China, and the Ph.D. degree in systems engineering from Northeastern University, Shenyang, in 2002 and 2007, respectively, where he is currently a Professor with the Liaoning Engineering Laboratory of Operations Analytics and Optimization for Smart Industry and the State Key Laboratory of Synthetical Aut...View more
Institute of Industrial and Systems Engineering, Northeastern University, Shenyang, China
Lixin Tang (SM’14) received the B.Eng. degree in industrial automation, the M.Eng. degree in systems engineering, and the Ph.D. degree in control theory and application from Northeastern University, Shenyang, China, in 1988, 1991, and 1996, respectively.
He is currently a Cheung Kong Scholars’ Chair Professor, the Vice President of Northeastern University, the Director of the Institute of Industrial Systems Engineering, an...Show More
Lixin Tang (SM’14) received the B.Eng. degree in industrial automation, the M.Eng. degree in systems engineering, and the Ph.D. degree in control theory and application from Northeastern University, Shenyang, China, in 1988, 1991, and 1996, respectively.
He is currently a Cheung Kong Scholars’ Chair Professor, the Vice President of Northeastern University, the Director of the Institute of Industrial Systems Engineering, an...View more
Contents Key Laboratory of Data Analytics and Optimization for Smart Industry, Ministry of Education, Liaoning Engineering Laboratory of Operation Analytics and Optimization for Smart Industry, Northeastern University, Shenyang, China
Linlin Li received the B.Sc. degree in computer and application and the M.Sc. degree in computer application technology from Northeastern University, Shenyang, China, in 2002 and 2005, respectively, where she is currently pursuing the Ph.D. degree in system engineering with the College of Information Science and Engineering.
She is also an Associate Professor with the School of Software, University of Science and Technology Liaoning, Anshan, China. Her research interests include multi-objective optimization, production scheduling, and intelligent optimization algorithms.
Linlin Li received the B.Sc. degree in computer and application and the M.Sc. degree in computer application technology from Northeastern University, Shenyang, China, in 2002 and 2005, respectively, where she is currently pursuing the Ph.D. degree in system engineering with the College of Information Science and Engineering.
She is also an Associate Professor with the School of Software, University of Science and Technology Liaoning, Anshan, China. Her research interests include multi-objective optimization, production scheduling, and intelligent optimization algorithms.View more
Key Laboratory of Data Analytics and Optimization for Smart Industry, Ministry of Education, Liaoning Engineering Laboratory of Operation Analytics and Optimization for Smart Industry, Northeastern University, Shenyang, China
Zan Wang received the B.S. degree in industrial engineering from Northeastern University, Shenyang, China, in 2015, where he is currently pursuing the master’s degree with the Liaoning Engineering Laboratory of Operations Analytics and Optimization for Smart Industry. His current research interests include multi-factor optimization, machine learning, and their applications.
Zan Wang received the B.S. degree in industrial engineering from Northeastern University, Shenyang, China, in 2015, where he is currently pursuing the master’s degree with the Liaoning Engineering Laboratory of Operations Analytics and Optimization for Smart Industry. His current research interests include multi-factor optimization, machine learning, and their applications.View more
Liaoning Key Laboratory of Manufacturing System and Logistics, Institute of Industrial and Systems Engineering, Northeastern University, Shenyang, China
Xianpeng Wang (M’ 11) received the B.S. degree in materials and control engineering from Shenyang University, Shenyang, China, and the Ph.D. degree in systems engineering from Northeastern University, Shenyang, in 2002 and 2007, respectively, where he is currently a Professor with the Liaoning Engineering Laboratory of Operations Analytics and Optimization for Smart Industry and the State Key Laboratory of Synthetical Automation for Process Industries.
His research interests include multi-objective optimization, machine learning, production scheduling, modeling and optimization in process industries based on data analytics, decision support systems, and process operation optimization. He has published more than 20 papers in international journals, such as the IEEE Transactions on Evolutionary Computation, the IEEE Transactions on Control Systems Technology, the European Journal of Operational Research, Applied Soft Computing, Computers & Operations Research, the IEEE Transactions on Automation Science and Engineering, Information Sciences, and Journal of the Operational Research Society.
Xianpeng Wang (M’ 11) received the B.S. degree in materials and control engineering from Shenyang University, Shenyang, China, and the Ph.D. degree in systems engineering from Northeastern University, Shenyang, in 2002 and 2007, respectively, where he is currently a Professor with the Liaoning Engineering Laboratory of Operations Analytics and Optimization for Smart Industry and the State Key Laboratory of Synthetical Automation for Process Industries.
His research interests include multi-objective optimization, machine learning, production scheduling, modeling and optimization in process industries based on data analytics, decision support systems, and process operation optimization. He has published more than 20 papers in international journals, such as the IEEE Transactions on Evolutionary Computation, the IEEE Transactions on Control Systems Technology, the European Journal of Operational Research, Applied Soft Computing, Computers & Operations Research, the IEEE Transactions on Automation Science and Engineering, Information Sciences, and Journal of the Operational Research Society.View more
Institute of Industrial and Systems Engineering, Northeastern University, Shenyang, China
Lixin Tang (SM’14) received the B.Eng. degree in industrial automation, the M.Eng. degree in systems engineering, and the Ph.D. degree in control theory and application from Northeastern University, Shenyang, China, in 1988, 1991, and 1996, respectively.
He is currently a Cheung Kong Scholars’ Chair Professor, the Vice President of Northeastern University, the Director of the Institute of Industrial Systems Engineering, and the Head of the Operation Analytics and Optimization Centre for Smart Industry, Northeastern University. He has published 79 papers in international journals, such as OR, M&SOM, INFORMS Journal on Computing, IISE Transactions, NRL, and the IEEE Transactions on Evolutionary Computation. His research interests include industrial big data science, data analytics and machine learning, reinforcement learning and dynamic optimization, computational intelligent optimization, plant-wide production and logistics planning, production and logistics batching and scheduling and engineering applications in manufacturing (steel, petroleum-chemical, nonferrous), energy, resources industry, and logistics systems.
Dr. Tang was selected into the list of 2014, 2015, and 2016 Most Cited Chinese Researchers by Elsevier. The paper published on flagship journal IIE Transactions (now renamed as IISE Transactions) won the Best Applications Paper Award of 2015–2016. He serves as an Associate Editor for the IISE Transactions, the IEEE Transactions on Evolutionary Computation, the IEEE Transactions on Cybernetics, the IEEE Transactions on Automation Science and Engineering, the Journal of Scheduling, the International Journal of Production Research, and the Journal of the Operational Research Society, serves in the Editorial Board of Annals of Operations Research, and serves as an Area Editor for the Asia-Pacific Journal of Operational Research.
Lixin Tang (SM’14) received the B.Eng. degree in industrial automation, the M.Eng. degree in systems engineering, and the Ph.D. degree in control theory and application from Northeastern University, Shenyang, China, in 1988, 1991, and 1996, respectively.
He is currently a Cheung Kong Scholars’ Chair Professor, the Vice President of Northeastern University, the Director of the Institute of Industrial Systems Engineering, and the Head of the Operation Analytics and Optimization Centre for Smart Industry, Northeastern University. He has published 79 papers in international journals, such as OR, M&SOM, INFORMS Journal on Computing, IISE Transactions, NRL, and the IEEE Transactions on Evolutionary Computation. His research interests include industrial big data science, data analytics and machine learning, reinforcement learning and dynamic optimization, computational intelligent optimization, plant-wide production and logistics planning, production and logistics batching and scheduling and engineering applications in manufacturing (steel, petroleum-chemical, nonferrous), energy, resources industry, and logistics systems.
Dr. Tang was selected into the list of 2014, 2015, and 2016 Most Cited Chinese Researchers by Elsevier. The paper published on flagship journal IIE Transactions (now renamed as IISE Transactions) won the Best Applications Paper Award of 2015–2016. He serves as an Associate Editor for the IISE Transactions, the IEEE Transactions on Evolutionary Computation, the IEEE Transactions on Cybernetics, the IEEE Transactions on Automation Science and Engineering, the Journal of Scheduling, the International Journal of Production Research, and the Journal of the Operational Research Society, serves in the Editorial Board of Annals of Operations Research, and serves as an Area Editor for the Asia-Pacific Journal of Operational Research.View more