Annals of Operations Research最新文献

The recycling and remanufacturing of electronic waste are critical for resource conservation and the sustainable development of both society and the environment. However, uncertainty about the quality of recycled products introduces risk aversion. To address this issue, the present study develops a differential decision-making model that distinguishes between manufacturers who consider, and those who ignore, the risk-averse behavior of recyclers. The analysis examines how recyclers’ risk aversion affects key factors in a closed-loop supply chain, including sales price, recovery rate, demand, and the profits and utilities of both manufacturers and recyclers. Our findings suggest that achieving optimal recovery rates, demand, and utility for both parties requires that carbon tax formulation aligns with recovery costs. Additionally, this tax serves as a critical benchmark for determining the repurchase price of waste products. When recyclers exhibit risk aversion, increasing this aversion results in higher product sales prices, but also leads to lower demand, recovery rates, and profits for both manufacturers and recyclers. In contrast, manufacturers who disregard recyclers’ risk aversion may lower product sales prices, thereby increasing recovery rates, demand, and recycler utility. However, acknowledging and addressing risk aversion has a positive effect on manufacturer profits and utility.

Disasters impose huge human and financial losses and hinder humanitarian logistics. This study aims to find an efficient solution for humanitarian relief logistics in disasters by reducing time and cost. A sustainable-resilient multi-commodity, multi-depot, multi-objective, mixed-integer programming model is proposed for humanitarian relief logistics networks. The model considers network disruption, backup facilities, and rescue operations within standard relief time and golden time. The model utilizes a heterogeneous fleet of vehicles at different speeds, considering physical and mental health services at mild, moderate, and severe levels, and hygiene items such as diapers and sanitary pads in shelters. These components are included in the model to achieve Sustainable Development Goals and sustainability, the most important of which is Good Health and Well-being. After linearization, a case study is conducted to assess the validity of the model. Our proposed model is designed for a two-echelon location-allocation problem integrating pre- and post-disaster actions and solved via the augmented ε-constraint method in CPLEX/GAMS. It is observed that the model effectively allocates demands within a reasonable time and cost, finds facility locations, and activates backup facilities when warehouses are damaged due to disruption. The obtained results of the multi-objective model illustrate a trade-off between the objective functions, where a slight decrease in the response time leads to significantly higher costs. The sensitivity analysis demonstrates that an increase in demand leads to higher variable costs and longer response time but does not affect fixed costs. Furthermore, increasing the number of facility disruptions extends the relief time.

This study investigates the efficiency and performance of waste supply chain management across eight major South Korean cities, focusing on the interplay between input variables, inefficiency determinants, and waste processing outputs. Employing a multidisciplinary framework grounded in Resource-Based View, Environmental Justice Theory, and Systems Theory, the research utilizes Stochastic Frontier Analysis (SFA), Grey Incidence Analysis (GIA), and Artificial Neural Network (ANN) to evaluate the relative importance of various influencing factors. SFA estimate results highlight that budget and manpower productivity significantly contribute to efficiency, while disparities in budget allocation and outdated infrastructure contribute to inefficiencies. GIA underscores the dominance of commercial incineration and landfill performance, driven by strict industrial regulations and waste-to-energy initiatives. Conversely, commercial recycling and domestic landfill perform the worst. ANN reveals that budget productivity and manpower productivity have stronger and more impactful relationships with efficiency scores in cities like Seoul, Busan, and Incheon. On the inefficiency side, high facility installation costs, operation costs, and miscellaneous costs demonstrate significant negative impact on overall effectiveness across multiple cities.

In simple games, larger coalitions typically wield more power, but do all players align their efforts effectively? Consider a voting scenario where a coalition forms, but needs more voters to pass a bill. The cohesion of the new group of voters hinges on whether all the new members can proficiently collaborate with the existing players to ensure the bill’s passage or if subgroups form that pursue an independent alternative, thus generating antagonism among the new voters. This research introduces two classes of coopetition indices– one relative and one absolute, the latter ranging from −1 to 1, to measure agents’ preferences for cooperation (when positive) or competition (when negative) with the remaining players. These indices, together with a generalized group value, provide a comprehensive picture of the relevance and the cohesion of groups. We discuss the relationship with similar group indices and provide proper coopetition Banzhaf and Shapley-Owen types of indices. By applying our indices to the apex game and symmetric majority games, we observe that cooperation and competition frequently balance each other out, leading to null values for the Shapley-Owen and Banzhaf coopetition indices. An electoral application with real world data is also considered.

Reverse logistics (RL) creates a number of opportunities for electronic equipment manufacturing enterprises and helps to augment the sustainability of a supply chain (SC). In India, outsourcing to Third Party Reverse Logistics Providers (3PRLPs) is a prominent initiative for a successful RL business model. However, small and mid-size enterprises (SMEs) face a number of risks in outsourcing RL activities. In this context, this study fills the literature gap by identifying and analysing the risk factors associated with outsourcing to 3PRLPs by SMEs in electronics sectors in India for a successful and sustainable reverse supply chain (RSC). Initially, 30 risk factors in the context of RL outsourcing are identified and clustered into 6 risk categories, namely “relationship and competence risks”, “economic risks”, “operational risks”, “organizational risks”, “social risks”, and “environmental risks”. Then, a weighted influence non-linear gauge system (WINGS) is used to understand the level of importance of each risk category and, simultaneously, they are also classified in cause and result groups. Similarly, risk factors within each risk category are evaluated. The findings indicate that SMEs in the electronics sector in India encounter several risks in outsourcing RL activities like uncertainty in returns, financial burden, stiff competitions, 3PRLP opportunism, and many more. Hence, an immediate intervention is recommended for SMEs in the electronics sector in India to overcome the risk factors under the “economic” and “relationship and competence” risk categories to implement sustainable and business efficient RL through outsourcing to 3PRLP. The implications drawn from the study will guide the RL team experts of SMEs to deal with risks in the course of outsourcing to 3PRLP.

Driven by the critical global climate, developing green supply chains has become an essential goal for companies. Artificial Intelligence (AI) techniques like ChatGPT have experienced tremendous development in recent years, and the AI content generation techniques have reached a new stage of application. While ChatGPT has made significant contributions to the fields of mass media, computer science, education and others, there is limited research on its application in the supply chain management. Therefore, this research aims to explore the management capabilities of green supply chain by proposing a new application framework for ChatGPT. In this study, empirical data were collected from 215 listed companies in China. By employing ChatGPT to analyse these data and comparing with benchmark statistical analysis methods, this paper reveals the significant potential of ChatGPT in green supply chain management. The empirical analysis results demonstrated that ChatGPT could assist companies in green assessment of internal supply chains and provide management suggestions by exploring green data, and thus assist companies to achieve more efficient green supply chain management. This study provided preliminary application attempts and validated the effectiveness of ChatGPT, which might encourage companies to consider the introduction of ChatGPT-liked large language models in green supply chain management to further promote the construction of green supply chains. Furthermore, this study explored potential research topics of ChatGPT in green supply chain management and seeks to help researchers to develop further research in this topic.

Multicommunication is one of the methods at our disposal to address the significant challenges of reliability and latency in today’s communications. This paper presents a game-theoretical analysis of multicommunication, where we assume that players in a TU-game are restricted in their communication by a multigraph, whose links may or may not have limitations on capacity, frequency, or transmission speed. We generalize the classical position value defined for graph games to assess the importance of different communication providers. Extending to this context the classical properties of component efficiency and balanced link contributions we can characterize the new value. For a wide variety of multicommunications including but not limited to all those where the connections are in series or parallel, the value can be characterized by substituting balanced link contributions for the more restrictive balanced link pack contributions. In the case of limitations in capacity, parallel characterizations are obtained in which component efficiency must be substituted by a certain inefficiency that takes these limitations into account.