EUROPEAN JOURNAL OF OPERATIONAL RESEARCH欧洲运筹学杂志
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH(英文缩写 EUR J OPER RES),ISSN 0377-2217,eISSN 1872-6860,中文译名:欧洲运筹学杂志 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-09-28 至 2026-09-28，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2021 | 6.363 | Q1 |
| 2022 | 6.400 | Q1 |
| 2023 | 6.000 | Q1 |
| 2024 | 6.000 | Q1 |
| 2025 | 7.000 | Q1 |
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 最新收录文献
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1. A review of attacker-defender games: Current state and paths forward.
PMID:日期:2024-03-01In this article, we review the literature which proposes attacker-defender games to protect against strategic adversarial threats. More specifically, we follow the systematic literature review methodology to collect and review 127 journal articles that have been published over the past 15 years. We start by briefly discussing the common application areas that are addressed in the literature, although our focus in this review lies heavily in the approaches that have been adopted to model and solve attacker-defender games. In studying these approaches, we begin by analyzing the following features of the proposed game formulations: the sequence of moves, number of players, nature of decision variables and objective functions, and time horizons. We then analyze the common assumptions of perfect rationality, risk neutrality, and complete information that are enforced within the majority of the articles, and report on state-of-the-art research which has begun relaxing these assumptions. We find that relaxing these assumptions presents further challenges, such as enforcing new assumptions regarding how uncertainties are modeled, and issues with intractability when models are reformulated to account for considerations such as risk preferences. Finally, we examine the methods that have been adopted to solve attacker-defender games. We find that the majority of the articles obtain closed-form solutions to their models, while there are also many articles that developed novel solution algorithms and heuristics. Upon synthesizing and analyzing the literature, we expose open questions in the field, and present promising future research directions that can advance current knowledge.
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2. The hammer and the jab: Are COVID-19 lockdowns and vaccinations complements or substitutes?
PMID:日期:2023-11-16The COVID-19 pandemic has devastated lives and economies around the world. Initially a primary response was locking down parts of the economy to reduce social interactions and, hence, the virus' spread. After vaccines have been developed and produced in sufficient quantity, they can largely replace broad lock downs. This paper explores how lockdown policies should be varied during the year or so gap between when a vaccine is approved and when all who wish have been vaccinated. Are vaccines and lockdowns substitutes during that crucial time, in the sense that lockdowns should be reduced as vaccination rates rise? Or might they be complementary with the prospect of imminent vaccination increasing the value of stricter lockdowns, since hospitalization and death averted then may be permanently prevented, not just delayed? We investigate this question with a simple dynamic optimization model that captures both epidemiological and economic considerations. In this model, increasing the rate of vaccine deployment may increase or reduce the optimal total lockdown intensity and duration, depending on the values of other model parameters. That vaccines and lockdowns can act as either substitutes or complements even in a relatively simple model casts doubt on whether in more complicated models or the real world one should expect them to always be just one or the other. Within our model, for parameter values reflecting conditions in developed countries, the typical finding is to ease lockdown intensity gradually after substantial shares of the population have been vaccinated, but other strategies can be optimal for other parameter values. Reserving vaccines for those who have not yet been infected barely outperforms simpler strategies that ignore prior infection status. For certain parameter combinations, there are instances in which two quite different policies can perform equally well, and sometimes very small increases in vaccine capacity can tip the optimal solution to one that involves much longer and more intense lockdowns.
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3. Fair-split distribution of multi-dose vaccines with prioritized age groups and dynamic demand: The case study of COVID-19.
PMID:日期:2023-11-01The emergence of the SARS-CoV-2 virus and new viral variations with higher transmission and mortality rates have highlighted the urgency to accelerate vaccination to mitigate the morbidity and mortality of the COVID-19 pandemic. For this purpose, this paper formulates a new multi-vaccine, multi-depot location-inventory-routing problem for vaccine distribution. The proposed model addresses a wide variety of vaccination concerns: prioritizing age groups, fair distribution, multi-dose injection, dynamic demand, etc. To solve large-size instances of the model, we employ a Benders decomposition algorithm with a number of acceleration techniques. To monitor the dynamic demand of vaccines, we propose a new adjusted susceptible-infectious-recovered (SIR) epidemiological model, where infected individuals are tested and quarantined. The solution to the optimal control problem dynamically allocates the vaccine demand to reach the endemic equilibrium point. Finally, to illustrate the applicability and performance of the proposed model and solution approach, the paper reports extensive numerical experiments on a real case study of the vaccination campaign in France. The computational results show that the proposed Benders decomposition algorithm is 12 times faster, and its solutions are, on average, 16% better in terms of quality than the Gurobi solver under a limited CPU time. In terms of vaccination strategies, our results suggest that delaying the recommended time interval between doses of injection by a factor of 1.5 reduces the unmet demand up to 50%. Furthermore, we observed that the mortality is a convex function of fairness and an appropriate level of fairness should be adapted through the vaccination.
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4. Risk-based allocation of COVID-19 personal protective equipment under supply shortages.
PMID:日期:2023-11-01The COVID-19 outbreak put healthcare systems across the globe under immense pressure to meet the unprecedented demand for critical supplies and personal protective equipment (PPE). The traditional cost-effective supply chain paradigm failed to respond to the increased demand, putting healthcare workers (HCW) at a much higher infection risk relative to the general population. Recognizing PPE shortages and high infection risk for HCWs, the World Health Organization (WHO) recommends allocations based on ethical principles. In this paper, we model the infection risk for HCWs as a function of usage and use it as the basis for distribution planning that balances government procurement decisions, hospitals' PPE usage policies, and WHO ethical allocation guidelines. We propose an infection risk model that integrates PPE allocation decisions with disease progression estimates to quantify infection risk among HCWs. The proposed risk function is used to derive closed-form allocation decisions under WHO ethical guidelines in both deterministic and stochastic settings. The modelling is then extended to dynamic distribution planning. Although nonlinear, we reformulate the resulting model to make it solvable using off-the-shelf software. The risk function successfully accounts for virus prevalence in space and in time and leads to allocations that are sensitive to the differences between regions. Comparative analysis shows that the allocation policies lead to significantly different levels of infection risk, especially under high virus prevalence. The best-outcome allocation policy that aims to minimize the total infected cases outperforms other policies under this objective and that of minimizing the maximum number of infections per period.
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5. Behavioral Analytics for Myopic Agents.
PMID:日期:2023-10-16Many multi-agent systems have a single coordinator providing incentives to a large number of agents. Two challenges faced by the coordinator are a finite budget from which to allocate incentives, and an initial lack of knowledge about the utility function of the agents. Here, we present a behavioral analytics approach for solving the coordinator's problem when the agents make decisions by maximizing utility functions that depend on prior system states, inputs, and other parameters that are initially unknown. Our behavioral analytics framework involves three steps: first, we develop a model that describes the decision-making process of an agent; second, we use data to estimate the model parameters for each agent and predict their future decisions; and third, we use these predictions to optimize a set of incentives that will be provided to each agent. The framework and approaches we propose in this paper can then adapt incentives as new information is collected. Furthermore, we prove that the incentives computed by this approach are asymptotically optimal with respect to a loss function that describes the coordinator's objective. We optimize incentives with a decomposition scheme, where each sub-problem solves the coordinator's problem for a single agent, and the master problem is a pure integer program. We conclude with a simulation study to evaluate the effectiveness of our approach for designing a personalized weight loss program. The results show that our approach maintains efficacy of the program while reducing its costs by up to 60%, while adaptive heuristics provide substantially less savings.
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6. A multiple criteria approach for building a pandemic impact assessment composite indicator: The case of COVID-19 in Portugal.
PMID:日期:2023-09-01The COVID-19 pandemic has caused major damage and disruption to social, economic, and health systems (among others). In addition, it has posed unprecedented challenges to public health and policy/decision-makers who have been responsible for designing and implementing measures to mitigate its strong negative impact. The Portuguese health authorities have used decision analysis techniques to assess the impact of the pandemic and implemented measures for counties, regions, or across the entire country. These decision tools have been subject to some criticism and many stakeholders requested novel approaches. In particular, those which considered the dynamic changes in the pandemic's behaviour due to new virus variants and vaccines. A multidisciplinary team formed by researchers from the COVID-19 Committee of Instituto Superior Técnico at the University of Lisbon (CCIST analyst team) and physicians from the Crisis Office of the Portuguese Medical Association (GCOM expert team) collaborated to create a new tool to help politicians and decision-makers to fight the pandemic. This paper presents the main steps that led to the building of a pandemic impact assessment composite indicator applied to the specific case of COVID-19 in Portugal. A multiple criteria approach based on an additive multi-attribute value theory aggregation model was used to build the pandemic assessment composite indicator. The parameters of the additive model were devised based on an interactive socio-technical and co-constructive process between the CCIST and GCOM team members. The deck of cards method was the adopted technical tool to assist in the assessment the value functions as well as in the assessment of the criteria weights. The final tool was presented at a press conference and had a powerful impact on the Portuguese and on the main health decision-making stakeholders in the country. In this paper, a completed mathematical and graphical description of this tool is presented.
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7. On the impact of resource relocation in facing health emergencies.
PMID:日期:2023-07-01The outbreak of SARS-CoV-2 and the corresponding surge in patients with severe symptoms of COVID-19 put a strain on health systems, requiring specialized material and human resources, often exceeding the locally available ones. Motivated by a real emergency response system employed in Northern Italy, we propose a mathematical programming approach for rebalancing the health resources among a network of hospitals in a large geographical area. It is meant for tactical planning in facing foreseen peaks of patients requiring specialized treatment. Our model has a clean combinatorial structure. At the same time, it considers the handling of patients by a dedicated home healthcare service, and the efficient exploitation of resource sharing. We introduce mathematical programming heuristic based on decomposition methods and column generation to drive very large-scale neighborhood search. We evaluate its embedding in a multi-objective optimization framework. We experiment on real world data of the COVID-19 in Northern Italy during 2020, whose aggregation and post processing is made openly available to the community. Our approach proves to be effective in tackling realistic instances, thus making it a reliable basis for actual decision support tools.
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8. Building viable stockpiles of personnel protective equipment.
PMID:日期:2023-06-16Many stockpiled personnel protective equipment (PPE) were of no use during COVID-19 because they have expired. The need for rethinking past approaches of building PPE stockpiles without planning for their timely rotation has become clear. We develop a game-theoretic pandemic preparedness model for single and multiple PPE products for a budget-constrained governmental organization (GO) supplied by a manufacturer. The GO maximizes preparedness, measured by the service rate of PPE, whereas the manufacturer maximizes profit. The manufacturer supplies the PPE stockpile in the first year. Thereafter, the manufacturer buys back a quantity of older PPE from the GO annually and sells the GO the same quantity of new PPE. The manufacturer sells older PPE in the market place. We find that this approach induces the manufacturer to rotate inventory in the stockpile. Joint determination of the stockpile size and its rotation results in no waste from expired PPE and is better than separately determining the stockpile size and then determining how to rotate it. Using insights from the single PPE model, we examine the optimal budget allocation among multiple PPE products. We also consider the effect of spot market prices of PPE during a pandemic on the optimal stockpile sizes. We find that spot market prices of PPE can have a significant effect on the optimal stockpile sizes. We examine the performance of the proposed approach in a manufacturers-distributor-GO supply chain and with an option for the GO to invest in the manufacturer's volume flexibility and show its effectiveness.
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9. Optimal timing of non-pharmaceutical interventions during an epidemic.
PMID:日期:2023-03-16In response to the recent outbreak of the SARS-CoV-2 virus governments have aimed to reduce the virus's spread through, , non-pharmaceutical intervention. We address the question when such measures should be implemented and, once implemented, when to remove them. These issues are viewed through a real-options lens and we develop an SIRD-like continuous-time Markov chain model to analyze a sequence of options: the option to intervene and introduce measures and, after intervention has started, the option to remove these. Measures can be imposed multiple times. We implement our model using estimates from empirical studies and, under fairly general assumptions, our main conclusions are that: (1) measures should be put in place not long after the first infections occur; (2) if the epidemic is discovered when there are many infected individuals already, then it is optimal never to introduce measures; (3) once the decision to introduce measures has been taken, these should stay in place until the number of susceptible or infected members of the population is close to zero; (4) it is never optimal to introduce a tier system to phase-in measures but it is optimal to use a tier system to phase-out measures; (5) a more infectious variant may reduce the duration of measures being in place; (6) the risk of infections being brought in by travelers should be curbed even when no other measures are in place. These results are robust to several variations of our base-case model.
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10. Seriation Using Tree-penalized Path Length.
PMID:日期:2023-03-01Given a sample of data points and an by dissimilarity matrix, data seriation methods produce a linear ordering of the objects, putting similar objects nearby in the ordering. One may visualize the reordered dissimilarity matrix with a heat map and thus understand the structure of the data, while still displaying the full matrix of dissimilarities. Good orderings produce heat maps that are easy to read and allow for clear interpretation. We consider two popular seriation methods, minimizing path length by solving the Traveling Salesman Problem (TSP), and Optimal Leaf Ordering (OLO), which minimizes path length among all orderings consistent with a given tree structure. Learning from the strengths and weaknesses of the two methods, we introduce a new hybrid seriation method, tree-penalized Path Length (tpPL). The objective is a linear combination of path length and the extent of violations of the tree structure, with a parameter that transitions the optimal paths smoothly from TSP to OLO. We present a detailed study over 44 synthetic datasets which are designed to bring out the strengths and weaknesses of the three methods, finding that the hybrid nature of tpPL enables it to overcome the weaknesses of TSP and OLO.