European Journal of Operational Research最新文献_第6页

Partially adaptive multistage stochastic programming 部分自适应多阶段随机程序设计

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2024-09-21 DOI: 10.1016/j.ejor.2024.09.034

Sezen Ece Kayacık , Beste Basciftci , Albert H. Schrotenboer , Evrim Ursavas

Multistage stochastic programming is a powerful tool allowing decision-makers to revise their decisions at each stage based on the realized uncertainty. However, organizations are not able to be fully flexible, as decisions cannot be revised too frequently in practice. Consequently, decision commitment becomes crucial to ensure that initially made decisions remain unchanged for a certain period of time. This paper introduces partially adaptive multistage stochastic programming, a new optimization paradigm that strikes an optimal balance between decision flexibility and commitment by determining the best stages to revise decisions depending on the allowed level of flexibility. We introduce a novel mathematical formulation and theoretical properties eliminating certain constraint sets. Furthermore, we develop a decomposition method that effectively handles mixed-integer partially adaptive multistage programs by adapting the integer L-shaped method and Benders decomposition. Computational experiments on stochastic lot-sizing and generation expansion planning problems show substantial advantages attained through optimal selections of revision times when flexibility is limited, while demonstrating computational efficiency attained by employing the proposed properties and solution methodology. By adhering to these optimal revision times, organizations can achieve performance levels comparable to fully flexible settings.

多阶段随机程序设计是一种强大的工具，允许决策者在每个阶段根据已实现的不确定性修改其决策。然而，组织无法做到完全灵活，因为在实践中不可能频繁修改决策。因此，决策承诺对于确保最初做出的决策在一定时期内保持不变至关重要。本文介绍了部分自适应多阶段随机程序设计，这是一种新的优化范例，它能根据允许的灵活性水平确定修改决策的最佳阶段，从而在决策灵活性和承诺之间取得最佳平衡。我们介绍了一种新的数学公式和理论特性，消除了某些约束集。此外，我们还开发了一种分解方法，通过调整整数 L 型方法和本德斯分解法，有效处理混合整数部分自适应多阶段程序。在随机批量规模和发电量扩展规划问题上的计算实验表明，当灵活性受到限制时，通过优化选择修正时间可以获得巨大优势，同时也证明了采用所提出的特性和求解方法所能达到的计算效率。通过遵守这些最佳修订时间，企业可以达到与完全灵活设置相当的性能水平。

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引用次数: 0

Stabilizing financial networks via mergers and acquisitions 通过并购稳定金融网络

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2024-09-21 DOI: 10.1016/j.ejor.2024.09.035

Markku Kallio , Aein Khabazian

A bi-level model is proposed to explore efficient policies for supporting negotiations on financial crisis resolution. In a principal–agent framework, this model minimizes the welfare loss function of a central authority (social planner, SP) through the simultaneous choice of subsidy levels and potential pairs of banks to merge. The SP’s choice of mergers needs to be incentive-compatible with the autonomous choices of banks, and the evaluation of the financial network must adhere to standard accounting principles. Incentive compatibility is enforced by two options for conditions, based on stable matching or competitive bidding. For the evaluation of the financial network, we employ an extended Eisenberg–Noe clearing payment equilibrium by considering bankruptcy costs and the seniority levels of liabilities. Additionally, liabilities are not cleared among solvent banks, and corporate bonds may be used for clearing payments. The bi-level model specifies conditions for the clearing equilibrium. For demonstration, we use major European banks, and a scenario linked to the adverse economic conditions used in the 2016 EU-wide stress testing.

本文提出了一个双层模型，以探讨支持解决金融危机谈判的有效政策。在委托代理框架下，该模型通过同时选择补贴水平和可能合并的银行对，使中央当局（社会规划者，SP）的福利损失函数最小化。社会计划者对兼并的选择必须与银行的自主选择相激励，而对金融网络的评估必须遵守标准会计原则。激励相容通过基于稳定匹配或竞标的两种条件选择来实现。在评估金融网络时，我们采用了扩展的艾森伯格-诺伊清算支付均衡，考虑了破产成本和负债的优先级。此外，负债不会在有偿付能力的银行之间清算，公司债券也可用于清算支付。双层模型规定了清算均衡的条件。为便于演示，我们使用了欧洲主要银行以及与 2016 年欧盟范围内压力测试中使用的不利经济条件相关的情景。

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引用次数: 0

Solving the parallel processor scheduling and bin packing problems with contiguity constraints: Mathematical models and computational studies 解决具有连续性约束的并行处理器调度和垃圾箱打包问题：数学模型和计算研究

IF 6.4 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2024-09-21 DOI: 10.1016/j.ejor.2024.09.013

Fatih Burak Akçay, Maxence Delorme

The parallel processor scheduling and bin packing problems with contiguity constraints are important in the field of combinatorial optimization because both problems can be used as components of effective exact decomposition approaches for several two-dimensional packing problems. In this study, we provide an extensive review of existing mathematical formulations for the two problems, together with some model enhancements and lower bounding techniques, and we empirically evaluate the computational behavior of each of these elements using a state-of-the-art solver on a large set of literature instances. We also assess whether recent developments such as meet-in-the middle patterns and the reflect formulation can be used to solve the two problems more effectively. Our experiments demonstrate that some features, such as the mathematical model used, have a major impact on whether an approach is able to solve an instance, whereas other features, such as the use of symmetry-breaking constraints, do not bring any empirical advantage despite being useful in theory. Overall, our goal is to help the research community design more effective yet simpler algorithms to solve the parallel processor scheduling and bin packing problems with contiguity constraints and closely related extensions so that, eventually, those can be integrated into a larger number of exact methods for two-dimensional packing problems.

具有连续性约束的并行处理器调度问题和垃圾箱打包问题在组合优化领域非常重要，因为这两个问题都可以作为若干二维打包问题的有效精确分解方法的组成部分。在本研究中，我们广泛回顾了这两个问题的现有数学公式，以及一些模型增强和下限技术，并使用最先进的求解器在大量文献实例集上对每个元素的计算行为进行了实证评估。我们还评估了中间相遇模式和反射表述等最新发展是否可用于更有效地解决这两个问题。我们的实验表明，某些特征（如所使用的数学模型）对一种方法能否解决实例有重大影响，而其他特征（如对称性约束的使用）尽管在理论上有用，但并没有带来任何经验上的优势。总之，我们的目标是帮助研究界设计出更有效、更简单的算法，以解决带有连续性约束的并行处理器调度和垃圾箱打包问题以及与之密切相关的扩展问题，从而最终将这些算法集成到更多的二维打包问题精确方法中。

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引用次数: 0

A tight formulation for the dial-a-ride problem 拨号乘车问题的严密表述

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2024-09-20 DOI: 10.1016/j.ejor.2024.09.028

Daniela Gaul , Kathrin Klamroth , Christian Pfeiffer , Michael Stiglmayr , Arne Schulz

Ridepooling services play an increasingly important role in modern transportation systems. With soaring demand and growing fleet sizes, the underlying route planning problems become increasingly challenging. In this context, we consider the dial-a-ride problem (DARP): Given a set of transportation requests with pick-up and delivery locations, passenger numbers, time windows, and maximum ride times, an optimal routing for a fleet of vehicles, including an optimized passenger assignment, needs to be determined. We present tight mixed-integer linear programming (MILP) formulations for the DARP by combining two state-of-the-art models into novel location-augmented-event-based formulations. Strong valid inequalities and lower and upper bounding techniques are derived to further improve the formulations. We then demonstrate the theoretical and computational superiority of the new models: First, the linear programming relaxations of the new formulations are stronger than existing location-based approaches. Second, extensive numerical experiments on benchmark instances show that computational times are on average reduced by 53.9% compared to state-of-the-art event-based approaches.

拼车服务在现代运输系统中发挥着越来越重要的作用。随着需求的激增和车队规模的扩大，潜在的路线规划问题变得越来越具有挑战性。在这种情况下，我们考虑了 "拨号乘车 "问题（DARP）：给定一组包含接送地点、乘客人数、时间窗口和最长乘车时间的运输请求，需要确定车队的最优路线，包括优化的乘客分配。我们通过将两个最先进的模型结合到基于位置-事件增强的新公式中，为 DARP 提出了严密的混合整数线性规划（MILP）公式。我们还推导出了强有效不等式和上下限技术，以进一步改进这些公式。然后，我们证明了新模型在理论和计算上的优越性：首先，新公式的线性规划松弛比现有的基于位置的方法更强。其次，在基准实例上进行的大量数值实验表明，与最先进的基于事件的方法相比，计算时间平均缩短了 53.9%。

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引用次数: 0

Fleet repositioning in the tramp ship routing and scheduling problem with bunker optimization: A matheuristic solution approach 带有燃料优化的杂货船路由和调度问题中的船队重新定位：一种数学启发式求解方法

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2024-09-20 DOI: 10.1016/j.ejor.2024.09.029

Simen Omholt-Jensen , Kjetil Fagerholt , Frank Meisel

This paper investigates an important planning problem faced by dry bulk shipping operators, referred to as the Tramp Ship Routing and Scheduling Problem with Bunker Optimization (TSRSPBO). The problem is to maximize the overall profit of a fleet of vessels by selecting cargoes and determining ship routes and schedules. We consider this problem under a set of practically relevant features such as flexibility in cargo quantities, as well as bunkering decisions on where to procure fuel and how much. As a particularly novel feature, we address the regional allocation of vessels at the end of the planning period to be well prepared for meeting (uncertain) future demand. To incorporate this, we consider the TSRSPBO as a two-stage stochastic programming problem, where cargo selection, routing, and bunkering decisions are solved in the first-stage problem, and the recourse cost of fleet repositioning is considered in the second stage. We present arc flow and path flow formulations, where the latter employs a priori generation of feasible routes as input. For solving realistically sized instances, we propose a matheuristic based on an Adaptive Large Neighborhood Search (ALNS) framework that iteratively generates columns and solves the path flow model. Computational experiments based on real data show that this matheuristic finds high-quality solutions for large test instances with 120 cargoes, 30 vessels, and ten bunker ports in less than one hour. Also, considering the TSRSPBO as a two-stage stochastic problem achieves the highest profits and is solved almost as quickly as the deterministic problem variant.

本文研究了干散货航运运营商面临的一个重要规划问题，即 "干散货船舶航线和船期优化问题（TSRSPBO）"。该问题的目的是通过选择货物、确定船舶航线和船期来实现船队整体利润的最大化。我们在考虑这一问题时，考虑了一系列与实际相关的特征，如货物数量的灵活性，以及在哪里采购燃料和采购多少燃料的加油决策。作为一个特别新颖的特征，我们解决了在计划期结束时的船舶区域分配问题，以便为满足（不确定的）未来需求做好充分准备。为此，我们将 TSRSPBO 视为一个两阶段随机编程问题，在第一阶段问题中解决货物选择、航线安排和加油决策，在第二阶段考虑船队重新定位的追索成本。我们提出了弧流式和路径流式，其中路径流式采用先验生成的可行路线作为输入。为了求解实际大小的实例，我们提出了一种基于自适应大邻域搜索（ALNS）框架的数学启发式，该框架可迭代生成列并求解路径流模型。基于真实数据的计算实验表明，对于包含 120 件货物、30 艘船舶和 10 个加油港的大型测试实例，该有限元法能在一小时内找到高质量的解决方案。此外，将 TSRSPBO 视为两阶段随机问题可获得最高利润，其求解速度几乎与确定性问题变体相同。

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引用次数: 0

Optimizing sequential decision-making under risk: Strategic allocation with switching penalties 优化风险下的顺序决策：带有转换惩罚的战略分配

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2024-09-20 DOI: 10.1016/j.ejor.2024.09.023

Milad Malekipirbazari

This paper considers the multiarmed bandit (MAB) problem augmented with a critical real-world consideration: the cost implications of switching decisions. Our work distinguishes itself by addressing the largely unexplored domain of risk-averse MAB problems compounded by switching penalties. Such scenarios are not just theoretical constructs but are reflective of numerous practical applications. Our contribution is threefold: firstly, we explore how switching costs and risk aversion influence decision-making in MAB problems. Secondly, we present novel theoretical results, including the development of the Risk-Averse Switching Index (RASI), which addresses the dual challenges of risk aversion and switching costs, demonstrating its near-optimal efficacy. This heuristic solution method is grounded in dynamic coherent risk measures, enabling a time-consistent evaluation of risk and reward. Lastly, through rigorous numerical experiments, we validate our algorithm’s effectiveness and practical applicability, providing decision-makers with valuable insights and tools for navigating the multifaceted landscape of risk-averse environments with inherent switching costs.

本文探讨的多臂强盗（MAB）问题增加了一个重要的现实考虑因素：转换决策的成本影响。我们的工作与众不同之处在于，它涉及到了因切换惩罚而变得更加复杂的风险规避 MAB 问题，而这一领域在很大程度上尚未被探索。这种情况不仅仅是理论上的构造，而且反映了大量的实际应用。我们的贡献有三个方面：首先，我们探讨了转换成本和风险规避如何影响 MAB 问题的决策。其次，我们提出了新颖的理论成果，包括开发了风险规避转换指数（RASI），它解决了风险规避和转换成本的双重挑战，并证明了其接近最优的功效。这种启发式求解方法以动态连贯风险度量为基础，能够对风险和回报进行时间一致的评估。最后，通过严格的数值实验，我们验证了算法的有效性和实际应用性，为决策者提供了宝贵的见解和工具，帮助他们在具有固有转换成本的风险规避环境中游刃有余。

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引用次数: 0

Fifty years of reliability in operations research 运筹学可靠性五十年

IF 6.4 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2024-09-20 DOI: 10.1016/j.ejor.2024.09.010

Terje Aven, David Rios Insua, Refik Soyer, Xiaoyan Zhu, Enrico Zio

This paper provides an overview of the historical evolution of reliability in the scientific area of operations research. Historical views and future perspectives are specifically offered with regards to reliability modeling and inference, treatment of uncertainty in reliability modelling and analysis, definition of importance measures for identifying those elements of a system which are critical for its reliability, optimization of the design, operation and maintenance of a system with respect to its reliability, adversarial issues, and the growing focus on machine learning for reliability modeling and optimization. The overview and perspectives given are rich but by no means they cover all the great developments and advancements done, nor they point at all still-open issues and coming challenges.

本文概述了可靠性在运筹学科学领域的历史演变。本文特别就可靠性建模与推理、可靠性建模与分析中的不确定性处理、确定系统中对其可靠性至关重要的要素的重要性度量、根据系统可靠性优化系统的设计、运行与维护、对抗性问题以及在可靠性建模与优化中对机器学习的日益关注等方面提出了历史观点和未来展望。这些概述和观点内容丰富，但绝非涵盖了所有重大发展和进步，也没有指出所有尚未解决的问题和即将面临的挑战。

引用次数: 0

Bank financial sustainability evaluation: Data envelopment analysis with random forest and Shapley additive explanations 银行财务可持续性评估：采用随机森林和沙普利加法解释的数据包络分析法

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2024-09-19 DOI: 10.1016/j.ejor.2024.09.030

Yu Shi , Vincent Charles , Joe Zhu

Ensuring financial sustainability is imperative for a financial institution's overall stability. To mitigate the risk of bank failure amid financial crises, effective management of financial sustainability performance becomes paramount. This study introduces a comprehensive framework for the accurate and efficient quantification, indexing, and evaluation of financial sustainability within the American banking industry. Our approach begins by conceptualizing financial sustainability as a multi-stage, multifactor structure. We construct a composite index through a three-stage network data envelopment analysis (DEA) and subsequently develop a random forest classification model to predict financial sustainability outcomes. The classification model attains an average testing recall rate of 84.34 %. Additionally, we employ SHapley Additive exPlanations (SHAP) to scrutinize the impacts of contextual variables on financial sustainability performance across various substages and the overall banking process, as well as to improve the interpretability and transparency of the classification results. SHAP results reveal the significance and effects of contextual variables, and noteworthy differences in contextual impacts emerge among different banking substages. Specifically, loans and leases, interest income, total liabilities, total assets, and market capitalization positively contribute to the deposit stage; revenue to assets positively influences the loan stage; and revenue per share positively affects the profitability stage. This study serves the managerial objective of assisting banks in capturing financial sustainability and identifying potential sources of unsustainability. By unveiling the “black box” of financial sustainability and deciphering its internal dynamics and interactions, banks can enhance their ability to monitor and control financial sustainability performance more effectively.

确保财务可持续性对金融机构的整体稳定性至关重要。为了降低金融危机中银行倒闭的风险，有效管理财务可持续性绩效变得至关重要。本研究引入了一个综合框架，用于准确有效地量化、指数化和评估美国银行业的财务可持续性。我们的方法首先将财务可持续性概念化为一个多阶段、多因素的结构。我们通过三阶段网络数据包络分析（DEA）构建了一个综合指数，随后开发了一个随机森林分类模型来预测财务可持续性的结果。该分类模型的平均测试召回率达到 84.34%。此外，我们还采用了 SHapley Additive exPlanations（SHAP）方法，以仔细研究各子阶段和整个银行业务流程中的环境变量对财务可持续发展绩效的影响，并提高分类结果的可解释性和透明度。SHAP 的结果揭示了环境变量的重要性和影响，不同银行子行业在环境影响方面出现了值得注意的差异。具体而言，贷款和租赁、利息收入、总负债、总资产和市值对存款阶段有积极影响；收入与资产比率对贷款阶段有积极影响；每股收入对盈利阶段有积极影响。本研究的管理目标是帮助银行把握财务可持续性并识别潜在的不可持续性来源。通过揭开金融可持续发展的 "黑匣子"，解读其内部动态和相互作用，银行可以提高更有效地监测和控制金融可持续发展绩效的能力。

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引用次数: 0

Existence of equilibrium in a dynamic supply chain game with vertical coordination, horizontal competition, and complementary goods 具有纵向协调、横向竞争和互补商品的动态供应链博弈中均衡的存在性

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2024-09-19 DOI: 10.1016/j.ejor.2024.09.027

Bertrand Crettez , Naila Hayek , Guiomar Martín-Herrán

We consider supply chain competition and vertical coordination in a linear–quadratic differential game setting. In this setting, supply chains produce complementary goods and each of them includes a single manufacturer and a single retailer who coordinate their decisions through a revenue-sharing contract with a wholesale price and a fixed sales revenue share. We study a multiple leader-follower Stackelberg game where the manufacturers are the leaders and the retailers are the followers. Competition occurs at both levels of the supply chains. Retailers play Nash and compete in price; manufacturers also play Nash but they compete in choosing their production capacities by exploiting the equilibrium price decisions made by the retailers. We show that open-loop Nash equilibria exist when the manufacturers only receive a wholesale price (there are no longer exploiting the equilibrium price decision made by the retailers, however). When the manufacturers receive both a wholesale-price and a share of the retailers’ sales revenues, equilibria generally no longer exist. The non-existence of an equilibrium stems from the fact that the manufacturers’ instant profits are discontinuous functions of their production capacities. This discontinuity leads to a major technical difficulty in that one cannot apply standard optimal control approaches to study the equilibria of the dynamic game. Our results illustrate the possibility that competition between supply chains might not be sustainable when they sell complementary products and rely on a revenue-sharing agreement.

我们考虑的是线性-二次微分博弈环境下的供应链竞争和纵向协调。在这种情况下，供应链生产互补商品，每条供应链都包括一个制造商和一个零售商，他们通过一份收入共享合同协调决策，该合同包含批发价格和固定的销售收入份额。我们研究的是一个多领导者--追随者的斯塔克尔伯格博弈，其中制造商是领导者，零售商是追随者。竞争发生在供应链的两个层面。零售商参与纳什博弈，在价格上展开竞争；制造商也参与纳什博弈，但他们利用零售商做出的均衡价格决策，在选择生产能力上展开竞争。我们的研究表明，当制造商只收到批发价时，存在开环纳什均衡（但不再利用零售商的均衡价格决策）。当制造商同时获得批发价和零售商的销售收入分成时，均衡一般就不存在了。不存在均衡的原因在于，制造商的即时利润是其生产能力的不连续函数。这种不连续性导致了一个重大的技术难题，即我们无法运用标准的最优控制方法来研究动态博弈的均衡。我们的研究结果表明，当供应链销售互补产品并依赖于收入共享协议时，它们之间的竞争可能无法持续。

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引用次数: 0

Simple fixes that accommodate switching costs in multi-armed bandits 适应多臂匪徒中转换成本的简单修复方法

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2024-09-19 DOI: 10.1016/j.ejor.2024.09.017

Ehsan Teymourian , Jian Yang

When switching costs are added to the multi-armed bandit (MAB) problem where the arms’ random reward distributions are previously unknown, usually quite different techniques than those for pure MAB are required. We find that two simple fixes on the existing upper-confidence-bound (UCB) policy can work well for MAB with switching costs (MAB-SC). Two cases should be distinguished. One is with positive-gap ambiguity where the performance gap between the leading and lagging arms is known to be at least some

δ > 0

. For this, our fix is to erect barriers that discourage frivolous arm switchings. The other is with zero-gap ambiguity where absolutely nothing is known. We remedy this by forcing the same arms to be pulled in increasingly prolonged intervals. As usual, the effectivenesses of our fixes are measured by the worst average regrets over long time horizons

T

. When the barriers are fixed at

δ / 2

, we can accomplish a

ln (T)

-sized regret bound for the positive-gap case. When intervals are such that

n

of them occupy

n^{2}

periods, we can achieve the best possible

T^{1 / 2}

-sized regret bound for the zero-gap case. Other than UCB, these fixes can be applied to a learning while doing (LWD) heuristic to reach satisfactory results as well. While not yet with the best theoretical guarantees, the LWD-based policies have empirically outperformed those based on UCB and other known alternatives. Numerically competitive policies still include ones resulting from interval-based fixes on Thompson sampling (TS).

在多臂强盗（MAB）问题中加入转换成本时，由于各臂的随机奖励分布是未知的，通常需要采用与纯 MAB 完全不同的技术。我们发现，对现有的置信上限（UCB）策略进行两个简单的修正，就能很好地解决有转换成本的多臂强盗（MAB）问题（MAB-SC）。需要区分两种情况。一种情况是正差距模糊性，即已知领先臂和落后臂之间的性能差距至少为某个 δ>0。对于这种情况，我们的解决办法是设置障碍，阻止轻率的臂切换。另一种情况是零间隙模糊性，在这种情况下，我们完全不知道任何事情。对此，我们的补救措施是强迫在越来越长的时间间隔内拉动相同的臂。像往常一样，我们的固定方法的有效性是通过长时间跨度 T 的最坏平均遗憾来衡量的。当障碍固定在 δ/2 时，我们可以在正间隙情况下实现 ln(T)-sized regret bound。当时间间隔为 n 个，其中 n 个占据 n2 个周期时，我们就能在零间隙情况下实现最佳的 T1/2 大小的遗憾约束。除 UCB 外，这些修正也可以应用于边做边学（LWD）启发式，以获得令人满意的结果。基于 LWD 的策略虽然尚未获得最佳的理论保证，但在经验上已经优于基于 UCB 和其他已知替代方法的策略。在数值上具有竞争力的策略还包括基于汤普森采样（Thompson sampling，TS）的区间固定策略。

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引用次数: 0