Article
Management
Hairong Feng, Yinlian Zeng, Xiaoqiang Cai, Qian Qian, Yongwu Zhou
Summary: This study examines profit allocation rules for joint replenishment among retailers under a carbon cap-and-trade policy, taking into account their altruistic behavior. The results show that joint replenishment can increase retailers' total profit and reduce carbon emissions. Two profit allocation rules are proposed, one lying in the core of the game and another based on altruistic considerations, indicating that people help others based on the generosity of others.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Fengmin Yao, Qi Tan, Tao Li, Bin Liu
Summary: This study examines the effects of asymmetric settings and horizontal interaction on strategy selection in a competing supply chain system. The results show that virtual bargaining, horizontal interaction, and asymmetric settings have a minor effect on strategy selection, but have notable ramifications for the performance of channel members, the overall channel, and the entire supply chain.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Green & Sustainable Science & Technology
Jingci Xie, Jianjian Liu, Xin Huo, Qingchun Meng, Mengyu Chu
Summary: This paper focuses on the optimal decision of carbon emission reduction and pricing in the dual-channel supply chain of fresh food through three different models. The results show that the sales price, carbon emission reduction, market demand, and profits of the supply chain under different levels of consumers' low-carbon preference coefficient and freshness level exhibit similar changes.
Article
Environmental Sciences
Liurui Deng, Chen Cao, Jiawu Dai
Summary: This paper uses the Stackelberg game theory to analyze the financing decisions of a manufacturer and a retailer in a supply chain. The results show that improving emission reduction efficiency leads to a shift from external to internal financing methods. The impact of green sensitivity on profit depends on carbon emission trading prices. Manufacturers' financing decisions are influenced by these prices rather than by emissions exceeding standards. Higher prices make internal financing easier to obtain while limiting external financing space.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Zhangwei Feng, Peng Jin, Guiping Li
Summary: This paper focuses on the management of fresh food supply chains and highlights the importance of adopting blockchain traceability technology and cold-chain preservation technology. The study finds that blockchain traceability technology can effectively restrain misreporting behavior and enhance product freshness, while cold-chain preservation technology improves product shelf life. Game theoretic models are developed to identify the optimal conditions for technology selection by suppliers and retailers.
Article
Computer Science, Interdisciplinary Applications
Yuhong Liu, Deqing Ma, Jinsong Hu, Ziyi Zhang
Summary: Research shows that competition between traditional and online channels can lead to higher prices for fresh food and incentivize firms to invest in product freshness and blockchain technology. In the presence of channel competition, the E-platform's sales mode and optimal strategies depend on competition, fee rates, and wholesale prices. Increasing fee rates can drive up pricing and encourage traditional retailers to invest in blockchain technology.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Green & Sustainable Science & Technology
Xin Huang
Summary: This paper studies a dual-market low-carbon supply chain operation in urban and rural markets, involving one manufacturer and two retailers. The research finds that government intervention can increase technology innovation efforts and decrease advertising efforts, and joint store promotion under government intervention can further improve the profits of the manufacturer and retailers. Furthermore, the manufacturer's technological innovation strategy relies more on the price and promotion preferences of urban consumers. The research results provide valuable suggestions for improving the economic and environmental performance of the low-carbon supply chain in the dual market.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Interdisciplinary Applications
Yinlian Zeng, Xiaoqiang Cai, Hairong Feng
Summary: This article explores joint replenishment among multiple retailers under different carbon constraints. By considering various carbon policies, optimal ordering strategies are determined, and the problem of cost allocation is studied. It is found that in the joint replenishment game with a carbon tax, a simple proportional rule belongs to the core. In the joint replenishment games with strict carbon cap, carbon cap-and-offset, and carbon cap-and-price, where the penalty rate is higher than the reward rate, cost allocation rules based on the Lagrangian multipliers are part of the core. Interestingly, in the joint replenishment game with carbon cap-and-price and a lower penalty rate, subadditivity may not be satisfied, and the core may be empty. This suggests that joint replenishment is not feasible in this situation. Additionally, the carbon emission allocation game under the strict carbon cap policy is further discussed, and an algorithm is proposed to generate an optimal coalition structure.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Rodrigo Ulloa, J. Rene Villalobos
Summary: Special denomination labels for fresh food products have gained attention in recent decades. This paper explores the use of optimization tools to assess the impact of these labels on supply chains, with a focus on local food labels and distance. The results suggest that relaxing strict local food label definitions can reduce CO2 emissions in the supply chain of fresh produce.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Review
Food Science & Technology
Jinjin Huang, Min Zhang, Arun S. Mujumdar, Yamei Ma
Summary: Fresh food is nutritious but difficult to store without quality degradation. New technologies for intelligent, energy-efficient, and nondestructive preservation and processing have become research priorities due to increasing health-consciousness of consumers. This review summarizes the quality change characteristics of postharvest fruits, vegetables, meats, and aquatic products, critically analyzes emerging preservation technologies, and evaluates their benefits, drawbacks, and future development trends.
CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION
(2023)
Article
Computer Science, Interdisciplinary Applications
Xiangmeng Huang, Shuai Yang, Zhanyu Wang
Summary: The study confirms that inflation significantly affects the pricing and replenishment strategy of perishable food, and the DCF model is more suitable for evaluating the profits of perishable food.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Green & Sustainable Science & Technology
Yang Lv, Xinhua Bi, Quanxi Li, Haowei Zhang
Summary: This paper examines the decision-making and recycling channel selection of a closed-loop supply chain under carbon allowance and carbon trading policies, and draws conclusions based on the manufacturer's profit and carbon emissions in different models.
Article
Green & Sustainable Science & Technology
Nainsi Gupta, Gunjan Soni, Sameer Mittal, Indrajit Mukherjee, Bharti Ramtiyal, Devesh Kumar
Summary: Food traceability in the supply chain is crucial in addressing issues like fraud, adulteration, customer demands, and food loss. The study emphasizes the significance of traceability in minimizing food loss through effective monitoring across the supply chain. The actions and decisions of each participant in the chain impact traceability, creating complexity as the number of players increases. Analyzing stakeholder strategies and understanding their influence on traceability is essential. This study employs game theory to analyze strategic combinations of actions and decision-making processes in adopting traceability, as well as factors influencing its adoption in the food supply chain.
Article
Mathematics
Liang Shen, Xiaodi Wang, Qinqin Liu, Yuyan Wang, Lingxue Lv, Rongyun Tang
Summary: The study constructs a game decision-making model for the low-carbon e-commerce supply chain (LCE-SC) considering the carbon trading mechanism and consumers' preference for low-carbon products. The results show that the establishment of carbon trading pilots alleviates the negative impact of unfair profit distribution and increasing commission rate within a reasonable range improves profitability. Additionally, the implementation of carbon trading is conducive to regional sustainable development and controlling environmental governance intensity promotes carbon productivity.
Article
Green & Sustainable Science & Technology
Hua Pan, Huimin Zhu, Minmin Teng
Summary: Carbon abatement is crucial for achieving the double carbon goal in the power sector, and blockchain technology is a promising tool to facilitate this. This study proposes four decision models to analyze the changes in electricity price, sustainability level, power sales, and profits in the electricity supply chain. The analysis shows that user preference for blockchain technology and increased uploading of low-carbon electricity information can significantly improve the sustainability level of the electricity supply chain.
Article
Management
Min Wang, Lindu Zhao
Summary: Cold chains are crucial in reducing food spoilage, attracting food safety sensitive consumers, and ensuring food safety in the food supply chain. By establishing an optimization model, optimal levels of investment in cold chain construction and advertisement, as well as pricing, can be determined to maximize profits for supply chain members. Collaborative cold chain investment and pricing are found to be superior strategies for the supply chain, especially in a food safety sensitive market.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2021)
Article
Management
Min Wang, Lindu Zhao
Summary: This paper discusses the packaging strategy of fresh food supply chains, including the use of DPCs or RPCs, purchasing or renting RPCs, and the influence of environmental policies. The research finds that penalties and rewards are needed to motivate the use of RPCs, and reusing RPCs has both cost-saving and deterioration effects.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2022)
Review
Management
Vinicius N. Motta, Miguel F. Anjos, Michel Gendreau
Summary: This survey presents a review of optimization approaches for the integration of demand response in power systems planning and highlights important future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Philipp Schulze, Armin Scholl, Rico Walter
Summary: This paper proposes an improved branch-and-bound algorithm, R-SALSA, for solving the simple assembly line balancing problem, which performs well in balancing workloads and providing initial solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Roshan Mahes, Michel Mandjes, Marko Boon, Peter Taylor
Summary: This paper discusses appointment scheduling and presents a phase-type-based approach to handle variations in service times. Numerical experiments with dynamic scheduling demonstrate the benefits of rescheduling.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Oleg S. Pianykh, Sebastian Perez, Chengzhao Richard Zhang
Summary: Efficient scheduling is crucial for optimizing resource allocation and system performance. This study focuses on critical utilization and efficient scheduling in discrete scheduling systems, and compares the results with classical queueing theory.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Review
Management
Hamed Jahani, Babak Abbasi, Jiuh-Biing Sheu, Walid Klibi
Summary: Supply chain network design is a large and growing area of research. This study comprehensively surveys and analyzes articles published from 2008 to 2021 to detect and report financial perspectives in SCND models. The study also identifies research gaps and offers future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Patrick Healy, Nicolas Jozefowiez, Pierre Laroche, Franc Marchetti, Sebastien Martin, Zsuzsanna Roka
Summary: The Connected Max-k-Cut Problem is an extension of the well-known Max-Cut Problem, where the objective is to partition a graph into k connected subgraphs by maximizing the cost of inter-partition edges. The researchers propose a new integer linear program and a branch-and-cut algorithm for this problem, and also use graph isomorphism to structure the instances and facilitate their resolution. Extensive computational experiments show that, if k > 2, their approach outperforms existing algorithms in terms of quality.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Victor J. Espana, Juan Aparicio, Xavier Barber, Miriam Esteve
Summary: This paper introduces a new methodology based on the machine learning technique MARS for estimating production functions that satisfy classical production theory axioms. The new approach overcomes the overfitting problem of DEA through generalized cross-validation and demonstrates better performance in reducing mean squared error and bias compared to DEA and C2NLS methods.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Stefano Nasini, Rabia Nessah
Summary: In this paper, the authors investigate the impact of time flexibility in job scheduling, showing that it can significantly affect operators' ability to solve the problem efficiently. They propose a new methodology based on convex quadratic programming approaches that allows for optimal solutions in large-scale instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Zhiqiang Liao, Sheng Dai, Timo Kuosmanen
Summary: Nonparametric regression subject to convexity or concavity constraints is gaining popularity in various fields. The conventional convex regression method often suffers from overfitting and outliers. This paper proposes the convex support vector regression method to address these issues and demonstrates its advantages in prediction accuracy and robustness through numerical experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Kuo-Hao Chang, Ying-Zheng Wu, Wen-Ray Su, Lee-Yaw Lin
Summary: The damage and destruction caused by earthquakes necessitates the evacuation of affected populations. Simulation models, such as the Stochastic Pedestrian Cell Transmission Model (SPCTM), can be utilized to enhance disaster and evacuation management. The analysis of SPCTM provides insights for government officials to formulate effective evacuation strategies.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Qinghua Wu, Mu He, Jin-Kao Hao, Yongliang Lu
Summary: This paper studies a variant of the orienteering problem known as the clustered orienteering problem. In this problem, customers are grouped into clusters and a profit is associated with each cluster, collected only when all customers in the cluster are served. The proposed evolutionary algorithm, incorporating a backbone-based crossover operator and a destroy-and-repair mutation operator, outperforms existing algorithms on benchmark instances and sets new records on some instances. It also demonstrates scalability on large instances and has shown superiority over three state-of-the-art COP algorithms. The algorithm is also successfully applied to a dynamic version of the COP considering stochastic travel time.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Bjorn Bokelmann, Stefan Lessmann
Summary: Estimating treatment effects is an important task for data analysts, and uplift models provide support for efficient allocation of treatments. However, evaluating uplift models is challenging due to variance issues. This paper theoretically analyzes the variance of uplift evaluation metrics, proposes variance reduction methods based on statistical adjustment, and demonstrates their benefits on simulated and real-world data.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Congzheng Liu, Wenqi Zhu
Summary: This paper proposes a feature-based non-parametric approach to minimizing the conditional value-at-risk in the newsvendor problem. The method is able to handle both linear and nonlinear profits without prior knowledge of the demand distribution. Results from numerical and real-life experiments demonstrate the robustness and effectiveness of the approach.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Laszlo Csato
Summary: This paper compares the performance of the eigenvalue method and the row geometric mean as two weighting procedures. Through numerical experiments, it is found that the priorities derived from the two eigenvectors in the eigenvalue method do not always agree, while the row geometric mean serves as a compromise between them.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Guowei Dou, Tsan-Ming Choi
Summary: This study investigates the impact of channel relationships between manufacturers on government policies and explores the effectiveness of positive incentives versus taxes in increasing social welfare. The findings suggest that competition may be more effective in improving sustainability and social welfare. Additionally, government incentives for green technology may not necessarily enhance sustainability.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
