https://orcid.org/0000-0002-6734-3492
![Sample our Economics, Finance,Business & Industry journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5931/TOC-Subject-Sample-2021-Economics-Finance-Business-Industry.jpg"})
ABSTRACT
A supply and demand mismatch, or imbalance of the amount of supplies in the market, is always an issue and can happen all the time. Capacity sharing is an effective way to address this problem, and the capacity sharing platform facilitates the optimal matching between multiple capacity buyers and sellers. In the context of Industry 4.0, many industries are adopting intelligent algorithms to assist in decision-making. This paper presents an optimal or near-optimal matching algorithm to cope with a large volume of capacity-sharing problems. The fairness of the matching solution is captured by including three objectives from platform, sellers and buyers. In this paper, a 2-dimensional crossover and an order-first mutation are developed and employed with genetic algorithms (GA), including GA and NSGA-II. Additionally, a novel repair mechanism is proposed by considering various constraints to transform infeasible solutions into feasible ones. Two matching schemes are studied based on whether orders from buyers can be split or not. The results show that both algorithms based on traditional GA and NSGA-II are effective for different schemes. In addition, it is found that GA has better performance in the case of ‘more sellers’ and NSGA-II shows better performance in the ‘more buyers’ case.
Acknowledgments
This research was supported by the Youth Foundation of Social Science and Humanity, China Ministry of Education (grant number 20YJC630166, 21YJC630084), Social Science Foundation of Shandong Province of China (grant number 20DGLJO10), the National Natural Science Foundation of China (grant number 72101136), the Youth Foundation of Shandong Natural Science Foundation of China (grant number ZR2021QG001, ZR2021QG045) and the Young Scholars Program of Shandong University.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statements
The datasets generated during and/or analyzed during the current study are available in the Mendeley Data repository, DOI: 10.17632/sx88drkkth.2.
Additional information
Funding
Notes on contributors
Lei Xie
Dr. Lei Xie is an associate Professor at School of Management, Shandong University. He has completed his Ph.D. from Tianjin University, China. His research interest is productions and operations management. He has more than 20 publications in relevant journals, including International Journal of Production Research, Transportation Research Part E: Logistics and Transportation Review, Computers & Industrial Engineering and Journal of Cleaner Production.
Jianghua Zhang
Professor Jianghua Zhang is the Vice Dean of School of Management of Shandong University, outstanding young and middle-aged scholar of Shandong University, and Zhongying young scholar. He also served as the Deputy Director of the Emergency Management Special Committee of the Chinese Society of Systems Engineering and the Vice Chairman of the Management and Decision Science Special Committee of the Chinese Society for Management Modernization. His main research directions are intelligent decision-making, big data analysis, intelligent medical health management, etc.
Qingchun Meng
Professor Qingchun Meng is currently the director of the Center for Value Co creation Network Research of Shandong University, and the director of the Key Laboratory of Social Hypernetwork Computing and Decision Simulation of Shandong Universities. He also served as the deputy secretary-general of the Research Association of the Unified Research Method and Economic Mathematics of the Chinese Preferred Law, the vice chairman and secretary-general of the Network Science Branch, the director of the Chinese Society of Management Science and Engineering, the deputy leader of the Supply Chain Management Professional Working Group of the Logistics Management and Engineering Education Guidance Committee of the Ministry of Education, the expert of the transformation of new and old kinetic energy into think tanks, the editorial board member of China Management Science, and the independent director of Aucma. His Main research directions are emergency supply chain management and decision-making, complex network and industrial economy.
Yan Jin
Dr. Yan Jin is a Professor in the School of Mechanical and Aerospace Engineering at Queen’s University Belfast. He has been working in the school as a research fellow (2007-08), a lecturer (2009-15), a senior lecturer (2015-18), and a reader (2018-21). He obtained both his Bachelor and master’s degree in mechanical engineering in Dalian University of Technology China, in 1998 and 2002 respectively, and received his PhD from Nanyang Technological University Singapore in 2007. Dr Jin’s research interest is in parallel kinematic machines, robotics, digital lean and green manufacturing, high performance machining, and production management.
Weibo Liu
Dr. Weibo Liu is an associate professor of the School of Management, Shandong University, and candidate of the future plan for young scholars of Shandong University. In 2017, he received a doctor's degree from Queen's University of Belfast in the United Kingdom. He has successively presided over the National Natural Science Foundation, the Humanities and Social Science Foundation of the Ministry of Education and the Natural Science Foundation of Shandong Province. His research interests include operation management, production system simulation and scheduling optimization, and machine learning.