Annals of Operations Research最新文献

Reducing carbon emissions in the manufacturing sector is an important pathway to achieving sustainable development goals (SDGs). Anchored in SDG 13, this study focuses on the operational and low-carbon research and development (R&D) issues faced by firms in a supply chain, comprising one supplier and one manufacturer, in two scenarios: cooperative decision making and independent decision making. The independent decision-making scenario is classified into three modes: supplier-independent R&D, manufacturer-independent R&D, and two firms simultaneously R&D. First, this study evaluates the various modes with regard to unit abatement levels, corporate profits, environmental impact, and consumer surplus. Next, the analysis investigates the influence of carbon tax and R&D cost coefficient on equilibrium strategy. Our findings indicate that under the cooperative mode, when the cost coefficient is below a certain threshold, a high carbon tax can effectively incentivize both firms to increase their carbon reduction efforts, thereby enhancing the overall profitability of the supply chain and advancing the achievement of the SDG 13. The simultaneous independent R&D can enable all parties to obtain a high unit abatement level than when a single firm conducts independent R&D. In addition, the simultaneous R&D mode of two firms can generate higher profits and consumer surplus than the R&D mode of a single firm, and can bring higher total supply chain profits than the cooperative mode when the R&D cost is low. After extending modes to the case where the two firms cooperate only in the field of R&D, this study finds that the unit abatement level reaches the maximum.

Competitive balance, which refers to the level of control teams have over a sports competition, is a crucial indicator for tournament organisers. According to previous studies, competitive balance has significantly declined in the UEFA Champions League group stage over the recent decades. Our paper introduces alternative indices to investigate this issue. Two ex ante measures are based on Elo ratings, and four dynamic concentration indicators compare the final group ranking to reasonable benchmarks. Using these indices, we find no evidence of any long-run trend in the competitive balance of the UEFA Champions League group stage between the 2003/04 and 2023/24 seasons.

This paper deals with a Poisson input infinite-buffer single-server queue, where the arrivals occur in singles and the server serves the customers in batches. The server serves customers in batches of maximum size “b” with a minimum threshold size “a”. The service time of each batch follows general distribution (including heavy-tailed distribution) independent of each other as well as of the arrival process. The probability generating function (pgf) of the queue-length distributions at an arbitrary epoch as well as at a post-departure epoch of a batch have been derived using the embedded Markov chain and the argument of the rate-in and rate-out principle. The Laplace-Stieltjes transform (LST) of the actual waiting-time distribution (in the queue) of a random customer has also been derived using functional relation between pgf’s. The proposed analysis is based on the roots of the characteristic equation associated with the LST of the waiting-time distribution (in the queue) of a random customer. Using LSTs, the closed-form expressions for the probability density functions and for an arbitrary number of moments of the waiting-time distributions have been presented. We have also done numerical implementation of this procedure for the case of a bulk service infinite-buffer queueing model, and obtained the probability density function for waiting-time distribution of a random customer in the queue.

The Board Packing Problem (BoPP) considers a rectangular board divided in cells with m rows and n columns. In this problem, a subset from a set of rectangles with different costs may be allocated on the cells, and in turns, each cell has an associated revenue obtained if a rectangle is placed on it. The objective of the BoPP is to allocate rectangles on the board, covering cells in order to maximize the total profit, measured as the revenues of the selected cells where the rectangle is placed minus the cost of purchasing such rectangles. The revenue of a cell is collected only once, and only if a rectangle is covering the cell. We propose a Variable Neighborhood Descent (VND) approach for solving the BoPP. Two constructive procedures are proposed for generating the initial solution for the VND: a totally greedy approach and a greedy randomized method to favor diversity. The experimental comparison analyses the contribution of each component of the final algorithm and then performs a competitive testing to evaluate the performance of the algorithm when comparing it with the best method found in the state of the art. The superiority of the proposal is supported by non-parametric statistical tests.

Promoting low-carbon innovation (LCI) in firms through government subsidies has emerged as a widely-used policy instrument for achieving sustainable development, directly contributing to the United Nations Sustainable Development Goals (SDGs), including SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation, and Infrastructure), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action). Considering a complementary supply chain consisting of a supplier and a manufacturer, where the manufacturer assembles components produced in-house and by the supplier into one final product. The government aims to enhance social welfare or LCI product innovation levels. To this end, the government has four potential subsidy strategies: supplier subsidy, manufacturer subsidy, consumer subsidy, and low-carbon infrastructure subsidy. Our research shows that first, although subsidizing low-carbon infrastructure can enhance social welfare, it offers minimal improvement in product LCI. Second, subsidies directed towards suppliers yield limited advancements in social welfare and LCI. Third, when consumers are price-sensitive, subsidizing the manufacturer can maximize both LCI and social welfare. Conversely, when consumers are LCI-sensitive, allocating subsidies toward the supplier is more beneficial. In summary, our research extends the existing literature on complementary supply chain management by identifying the optimal subsidy for the government to achieve its goals, offering tangible insights into practical pathways for realizing SDG 7, 9, 12, and 13 through targeted policy design.

This study considers the impact of supply and demand uncertainty on last-mile distribution in a disaster-relief supply chain with multiple Staging Areas (SAs) and one Point of Distribution (POD). The SAs function as temporary warehouses for receiving and organizing relief supplies that are subsequently transported to the POD where they are distributed to meet the stochastic demands of disaster survivors. The goal of this paper is to evaluate the effectiveness of policies for dispatching vehicles from the SAs to the POD in an effort to minimize unsatisfied demand at the POD. Prior literature suggests that continuously dispatching vehicles is an effective and pragmatic policy, but it has not been tested on a relief network with multiple Staging Areas. This study establishes criteria under which continuous dispatching (CD) is an optimal policy and examines its performance through computational experiments. We solve problem instances using approximate dynamic programming since the stochastic dynamic programming model cannot be solved directly. Our findings suggest that the CD policy does not perform as well as in previous studies, but may be the best available option from a practical perspective.

Gerrymandering—the deliberate manipulation of electoral district boundaries for political advantage—is a persistent challenge in U.S. elections. In this work, we introduce and analyze Votemandering, a strategic blend of gerrymandering and targeted political campaigning devised to gain more seats by circumventing fairness measures. Votemandering leverages accurate demographic and socio-political data, bolstered by advancements in technology and data analytics, to influence voter decisions in pursuit of subtle gerrymandering strategies. We formulate votemandering as a Mixed Integer Program (MIP) that performs fairness-constrained gerrymandering over multiple election rounds. We analyze the influence of various redistricting constraints and parameters on votemandering efficacy. We explore the interconnectedness of gerrymandering, substantial campaign budgets, and strategic campaigning, illustrating their collective potential to generate biased electoral maps. A case study of Wisconsin State Senate redistricting reveals significant votemandering potential. Our findings underscore the need for reforms in the redistricting process beyond enforcing thresholds for specific fairness metrics.

The purpose of this paper is to investigate the impact of sentiment metrics derived from social media on stock market attributes, including returns and trading volumes, within three liquidity classes in the Russian emerging market. In this paper, we conduct a textual analysis of users' posts from two Russian-language online platforms: Tinkoff Pulse and MFD. We compare different artificial intelligence algorithms to solve the problem of classifying large textual data. This allows us to determine that the Stacking ensemble method with unoptimised hyperparameters of the metaclassifier gives the best results when classifying text data (processed with TF-IDF), achievincy of about 62% for the test set. With this method, we construct a series of sentiment metrics for retail investors to study their impact on stock returns and trading volumes. The results show that investor sentiment is a significant factor explaining stock returns in most quantiles. In the process of analysing retail investor sentiment, it was found that attention and divergence indices affect retail investor behaviour for different quantiles of stock returns and trading volumes. For example, attention indicators have quite different effects on stock returns for different quantiles, suggesting the presence of several heterogeneous groups of retail investors. Young traders tend to rely on the opinions of Tinkoff Pulse users regarding first-tier (blue chip) stocks, which reflects investors' cognitive biases quite accurately. However, investors who express confidence in sentiment on the MFD platform have a different cognitive pattern, which is explained by the characterisation of users on the MFD platform. These users include older individuals with more trading experience who are more reticent to social media optimism and are more likely to perceive optimism as a signal to sell stocks. Based on the findings, this paper enhances the understanding of the role of retail investor liquidity in emerging financial markets. The lack of analysis of private investors' sentiment and explanation of market trends may not cover a significant gap in knowledge about the psychology of market participants in liquidity classes. Our results provide a foundation for future research that should be useful for investors, regulators, and developers of online social platforms.

We study capacity coordination in a dynamic duopoly with perfect Cournot complements where firms face investment adjustment costs when choosing their production capacities. We show that optimal capacities must become identical from a certain date on. We perform a numerical analysis of the optimal investment and capital paths and the optimal date at which capacities become equal. We find that eliminating overcapacity does not always mean decreasing the highest initial capacity (this is especially true when the firm with the lowest initial capacity has the highest depreciation rate). Moreover, it is possible that the investment of the firm with the lowest initial capacity is non-monotonic.

Workforce planning deals with determining the number of employees and associated skills necessary to meet the future operational needs of an organization. A workforce system consists of six elements: recruitment, attrition, promotion, training, retention, and scheduling. Historically, several workforce modeling and analysis methodologies have been developed to capture these elements. This paper reviews the results of workforce and manpower models published within peer-reviewed literature between 1959 and 2021 to provide an in-depth analysis of current models. The focus of this review is on analytical, simulation, and empirical models found in literature that were collected based on a citation requirement and keyword search criteria. Results demonstrate the trends in workforce modeling research and discuss the common uses of each model type and the advantages/disadvantages related to each model. Based on the common attributes of workforce systems, the discussion focuses on the most frequently used model type for each element and the best use for each model. Finally, recommendations are made for the development of workforce models that allow the most comprehensive view of the workforce systems of the future.