Article
Green & Sustainable Science & Technology
Pyung-Hoi Koo
Summary: This study investigates the coordination of a two-stage supply chain with capacity investment and bargaining power by introducing a capacity cost-sharing (CCS) contract. The study finds that the wholesale price and the manufacturer's CCS ratio are negatively proportional to each other, and increasing the CCS ratio can increase the manufacturer's expected profit. The study also identifies a CCS contract that can achieve supply chain coordination within a specific range of bargaining power.
Article
Mathematics
Wentao Yi, Zhongwei Feng, Chunqiao Tan, Yuzhong Yang
Summary: This paper investigates a two-echelon green supply chain with loss-averse members and analyzes the optimal strategies and profits in different scenarios. The impact of loss aversion and green efficiency coefficient of products on the supply chain is also studied, showing critical influences on retail and wholesale prices, as well as product green degree.
Article
Computer Science, Interdisciplinary Applications
Asif Iqbal Malik, Biswajit Sarkar, Muhammad Waqas Iqbal, Mehran Ullah, Irfanullah Khan, Muhammad Babar Ramzan
Summary: This paper focuses on coordination in a two-member supply chain with a flexible production system under buyer's service level constraint and stochastic demand. Multiple inspection policy and discrete investment function are used to improve cost-sharing scenario. The study develops three SC models and the results show that the centralized cooperative model based on Nash bargaining significantly improves the overall profit of the SC.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Management
Walter J. Gutjahr, Raimund M. Kovacevic, David Wozabal
Summary: This paper addresses the problem of bargaining in economics and management. It proposes a solution that integrates optimal managerial decision making into bargaining situations with random outcomes and explicitly models the impact of risk aversion. The proposed solution is based on coherent acceptability functionals and a set of axioms that extend the Nash bargaining theory. It provides concrete bargaining solutions for a wide range of practical problems and characterizes special cases where the random payoffs of players are simple functions of overall project profit. The findings show that there is no conflict of interest between players about management decisions and that risk aversion facilitates cooperation.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2022)
Article
Green & Sustainable Science & Technology
Jiali Qu, Benyong Hu, Chao Meng
Summary: Customer value is crucial in maintaining competitive advantages in the retail industry, influenced by factors like product price and innovation. Revenue sharing contracts are ineffective in coordinating the supply chain in a non-cooperative game, but a unique equilibrium can be found through Nash bargaining, leading to optimal consumer surplus.
Article
Computer Science, Interdisciplinary Applications
Andrew Allman, Qi Zhang
Summary: Demand response is an essential way to integrate renewable energy into the power grid. This research focuses on coordinating operating schedules of different processes to ensure fair sharing of benefits and proposes distributed solutions to protect data privacy. Computational studies and a case study demonstrate the feasibility and applicability of the proposed approaches.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Article
Management
Domenico De Giovanni, Elena Iakimova
Summary: This study examines the joint effect of uncertainty, competition, and risk-aversion on the optimal time and size of firms in a duopoly. It finds that increasing risk-aversion affects the leader's choice between deterring and accommodating the follower's entry, resulting in reduced equilibrium investment sizes and timing.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
Article
Energy & Fuels
Naoki Makimoto, Ryuta Takashima
Summary: The penetration of renewable energy sources into the power market has a significant impact on existing power generations. Power producers are facing challenges in recovering capital costs due to high operating costs and underinvestment. One solution is the implementation of a capacity mechanism, where power generation capacities can be sold through a market or bilateral contracts. This study examines investment in a power plant in both the electricity and capacity markets, analyzing the effects of investment opportunities, uncertainty, and risk aversion. The results show that the investment timing differs between the energy-only market and the capacity market, depending on the level of risk aversion.
Article
Automation & Control Systems
Stefanny Ramirez, Dario Bauso
Summary: This study proposes an optimal order quantity solution for the coordinated maintenance problem of multi-turbine offshore wind-farms by modeling the turbine deterioration process and using the risk-averse newsvendor model. The theory of robust dynamic coalitional games is applied to design a fair and stable cost allocation mechanism for the coalition.
Article
Energy & Fuels
AmirAli Nazari, Reza Keypour, Nima Amjady
Summary: The paper proposes a cooperative community storage expansion plan to jointly invest in energy storage systems, alleviating the burden of high investment costs and increasing overall economic benefits. The modified Nash bargaining theory approach ensures fair implementation of the cooperative framework, highlighting the advantages of cooperation.
Article
Energy & Fuels
Zhengmao Li, Lei Wu, Yan Xu, Luhao Wang, Nan Yang
Summary: This paper discusses a tri-layer non-cooperative energy trading approach among multiple grid-tied multi-energy microgrids in the restructured integrated energy market. The approach considers uncertainties from renewable energy, market prices, and electric energy loads via risk-averse stochastic programming. The paper presents comprehensive operation models of individual microgrids and proposes a tri-layer Cournot Nash game-based energy bidding method to ensure fair multi-energy trading and deal with uncertainty effects.
Article
Computer Science, Information Systems
Xuanheng Li, Ruyi Xiao, Miao Pan, Nan Zhao
Summary: The emerging Internet of Things (IoT) era has led to the development of many computation-intensive applications, and mobile edge computing (MEC) is a promising solution for supporting these applications. However, due to the uncertainty of user demand, application service providers (ASPs) face challenges in determining the amount of resources to rent in different regions and times. In this article, a data-driven risk-averse MEC resource investment (DRAI) strategy is proposed to address this issue, using statistical characteristics derived from historical data to construct an ambiguity set and developing a data-driven distributionally robust solution for the best strategy.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Thermodynamics
Yongli Wang, Minhan Zhou, Fuli Zhang, Yuli Zhang, Yuze Ma, Huanran Dong, Danyang Zhang, Lin Liu
Summary: The reform of Transmission and Distribution (T&D) tariffs in China has put pressure on the revenue and operations of power grid companies. Research is needed to alleviate the negative impact and achieve sustainable development. The paper developed models to calculate investment capacity, coordination, and optimization, and proposed investment strategies and policy recommendations through empirical analysis.
Article
Engineering, Industrial
Shouting Zhao, Juliang Zhang, T. C. E. Cheng
Summary: In this study, we investigate the coordination problem in supply chains. We find that production cost uncertainty exacerbates the incentive conflict in the supply chain, but centralized decision-making may increase expected profits. By designing an incomplete contract that allows for renegotiation after production cost realization, we are able to achieve the best outcome. We also explore the impact of contract incompleteness, renegotiation freedom, and residual control rights on supply chain performance, and demonstrate that our proposed incomplete contract can effectively avoid hold-up problems.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Management
Weixin Shang, Gangshu (George) Cai
Summary: The study found that price matching negotiation can benefit the seller but hurt all buyers, while all firms can benefit from it under coordination. However, PM leads to less consumer utility and social welfare compared with simultaneous negotiation, unless the second buyer in PM is considerably weaker than the first buyer.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2022)
Article
Engineering, Electrical & Electronic
Kai Pan, Yongpei Guan, Jean-Paul Watson, Jianhui Wang
IEEE TRANSACTIONS ON POWER SYSTEMS
(2016)
Article
Automation & Control Systems
Kai Pan, Yongpei Guan
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2017)
Article
Engineering, Industrial
Yongpei Guan, Kai Pan, Kezhuo Zhou
Article
Economics
Lingxiao Wu, Kai Pan, Shuaian Wang, Dong Yang
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2018)
Article
Management
Lei Fan, Kai Pan, Yongpei Guan
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2019)
Article
Automation & Control Systems
Ziliang Jin, Kai Pan, Lei Fan, Tao Ding
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2019)
Article
Economics
Xiangyong Li, Yi Ding, Kai Pan, Dapei Jiang, Y. P. Aneja
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2020)
Article
Engineering, Industrial
Jianqiu Huang, Kai Pan, Yongpei Guan
Summary: Renewable energy is increasingly being used to generate electricity for its significant economic and environmental benefits. To enhance reliability and efficiency in power system operations, an ancillary service market was introduced alongside day-ahead and real-time energy markets. By optimizing these markets through a unit commitment problem with regulation reserve, the study explores the polyhedral structure of the co-optimization model and develops strong valid inequalities to improve solution efficiency. Computational experiments demonstrate the effectiveness of the approach in enhancing the co-optimization of energy and ancillary service markets.
Article
Management
Huaxiao Shen, Yanzhi Li, Youhua (Frank) Chen, Kai Pan
Summary: In this study, researchers propose an integrated planning model to strike a balance between short-term profit and advertising effectiveness in the online display advertising industry. By utilizing robust optimization model and linear programming, they address the challenge posed by uncertainties in the supply of advertising resources.
OPERATIONS RESEARCH
(2021)
Article
Engineering, Manufacturing
Peng Wang, Kai Pan, Zhenzhen Yan, Yun Fong Lim
Summary: Maximizing system productivity or minimizing inter-completion time variability is the goal. Through analytical derivation of throughput and coefficient of variation, optimal strategies for assigning work content based on worker speeds have been identified.
PRODUCTION AND OPERATIONS MANAGEMENT
(2022)
Article
Computer Science, Interdisciplinary Applications
Meysam Cheramin, Jianqiang Cheng, Ruiwei Jiang, Kai Pan
Summary: Distributionally robust optimization is a modeling framework for decision making under uncertainty. This paper proposes computationally efficient approximations for large-scale DRO problems, which split the random vector into smaller pieces and use principal component analysis to reduce dimensionality. The results demonstrate the practical applicability and significant reduction in computational time of the proposed approximations.
INFORMS JOURNAL ON COMPUTING
(2022)
Article
Computer Science, Interdisciplinary Applications
Jianqiu Huang, Kai Pan, Yongpei Guan
Summary: This study developed a multistage stochastic optimization model to help system operators efficiently schedule power-generation assets under uncertainty. The research also explored the geometric structures of single and multiple generators to enhance computational efficiency.
INFORMS JOURNAL ON COMPUTING
(2021)
Article
Engineering, Electrical & Electronic
Abolhassan Mohammadi Fathabad, Jianqiang Cheng, Kai Pan, Feng Qiu
IEEE TRANSACTIONS ON POWER SYSTEMS
(2020)
Proceedings Paper
Computer Science, Hardware & Architecture
Xiang Li, Tianyi Pan, Guangmo (Amo) Tong, Kai Pan
2019 39TH IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS 2019)
(2019)
