Annals of Operations Research最新文献

This paper developed a closed-loop supply chain network (CLSCN) optimization model with corporate social responsibility (CSR), recycling, remanufacturing, refurbishing, and transaction cost on a supply chain consisting of manufacturers, retailers, a new product demand market, and a retailer-refurbished product demand market. The manufacturers produce substitutable products using raw materials from two sources, new and recycled. The retailers, in turn, face the demands of new products and retailer-refurbished products, and recycle from the new product demand market. We investigated a number of cases, and our results indicate that CSR can enhance CLSCN performance but more to the party closest to the demand market. It also shows that consumer behavior, competition, CSR investment, and sustainable practices (new material procurement, recycling, refurbishing, re-manufacturing, and environmental costs), play an essential role in CSR and closing the loop. With higher landfill cost, more willingness to return from consumers, less disutility for consumers to return, higher level of recycling and refurbishing, and higher re-manufacturing rate, CSR level tends to improve. Policy-makers can use these findings to encourage firms to improve CSR in CLSCN.

This contribution observes that plant capacity notions based on traditional radial efficiency measures may leave substantial amounts of slacks or unmeasured inefficiency. These unmeasured inefficiencies can result in inaccurate assessments of production capabilities, potentially leading to suboptimal operational and strategic decisions. To remedy this problem, we define new nonradial output-oriented and input-oriented plant capacity concepts based on nonradial Färe-Lovell efficiency measures. By leveraging nonradial measures, our approach captures multidimensional inefficiencies, providing a more nuanced and accurate evaluation of production performance across various input and output dimensions. Furthermore, we also explore how the introduction of nonradial attainability levels can render the attainable output-oriented plant capacity concept more flexible. This flexibility allows for the incorporation of realistic operational constraints, ensuring that capacity assessments are both practical and adaptable to diverse production environments. An empirical illustration on a secondary data set illustrates the pertinent differences between radial and nonradial plant capacity notions. Our empirical analysis demonstrates that nonradial measures offer a more detailed understanding of capacity utilization. In particular, it shows that nonradial plant capacity concepts are especially important on a nonconvex technology.

We introduce this volume of the Annals of Operations Research that collects updated versions of the invited surveys that appeared in the journal 4OR—A Quarterly Journal of Operations Research.

Retailers play a crucial role in the economy, and their ability to effectively manage supply disruptions can significantly impact their performance and competitiveness. This study delves into the complex dynamics of retail markets, particularly in duopoly settings, where two major retailers interact strategically to maximize their profits. The goal is to understand how supply disruptions influence not only pricing and advertising strategies but also sourcing decisions. Three game structures are presented to analyze interactions between retailers, aiming to maximize total profit by determining the optimal sale price and advertising investment. The paper introduces a mathematical formulation for these games and a methodology to find the optimal solution based on the sourcing strategy (single, dual, or multiple sourcing strategy).2

An extensive numerical example with discussion and sensitivity analysis is provided. The study's results can assist decision-makers in selecting the most appropriate sourcing strategy in the presence of disruptions. The optimal pricing and advertising investment in both disruption and non-disruption scenarios for retailers are identified. The study concludes that acting as the leader in the Stackelberg game rather than Nash leads to higher profits. Moreover, dual sourcing is more advantageous than multiple sourcing for retailers. The managerial insights offer useful recommendations for retailers to improve their position in the competitive market.

In this paper, we investigate the mixed regular-singular control non-zero sum stochastic differential games problem under partial information where both the state dynamics and the performance functional contain time delay and mean field. We prove the existence and uniqueness of the solution of singular mean-field stochastic differential delayed equations and general reflected anticipated mean-field backward stochastic differential equations. By using Pontryagin’s maximum principle and Malliavin calculus, we establish sufficient maximum principles and necessary maximum principles about the non-zero sum game. Consequently, we find corresponding Nash equilibrium points and saddle points. Furthermore, we apply the results to study an optimal investment and dividend problem under model uncertainty.

Our framework deals with stochastic dynamic inventory models for stocking decisions of a retailer selling a single perishable product in the presence of strategic customers who time their purchases. Each short period, the retailer determines a stocking quantity before random demand is realized. Strategic customers use their reference on product availability to purchase at a regular price or wait for a markdown and learn from the retailer’s stocking quantity to update their reference. We characterize the structural properties such as the concavity of single- and two-period profit functions. On an infinite horizon, we show that a steady-state reference distribution is ergodic and an optimal stocking quantity is unique for a given reference. We conduct extensive numerical studies on an infinite horizon to compare an optimal dynamic policy and the corresponding optimal static policy which sets a fixed stocking quantity over time. A near-optimal performance of optimal static policy with an average profit gap of less than 1% is remarkable and contrasts with that in the two-period model which may be far worse. Thus, a well-chosen fixed stocking quantity on a planning horizon with many short periods tends to yield a high performance without having to change stocking quantities over time.

We have proposed the maintenance effort assessment model based on two Wiener processes for the operation of open source software (OSS) used in the edge computing in the past. In particular, we consider that this proposed model can assess the reliability by using three dimensional graph. Then, we have proposed two-dimensional modeling based on the effort management in the past. In this paper, we propose new expanded maintenance model considering OSS edge computing by expanding the existing two Wiener processes model in order to consider the network environment under the edge OSS operation. Especially, it is important to control the amount of maintenance effort expense in the long-term phase. Then, we propose the optimization method based on the past two-dimensional Wiener processes model. Thereby, it will be helpful to assess the operation effort expenditures with network environment of edge OSS service. Moreover, actual effort data sets are analyzed to show numerical examples of the proposed optimization method considering the network environment under the edge OSS operation.