EURO Journal on Decision Processes最新文献

Projecting decisions. Unfolding architectural design practice in decision-making processes 预测决策。在决策过程中展开建筑设计实践

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EURO Journal on Decision Processes

Pub Date : 2026-01-01 DOI: 10.1016/j.ejdp.2026.100068

Elena Todella

This study explores the role of specific design documents – as visual artefacts – in shaping decision-making processes, highlighting how they can, at key moments, overcome conflicts by negotiating different perspectives. Architectural design research has undergone significant paradigm shifts, primarily through traditional sociological and anthropological approaches to professional practices in engineering and architecture. While scholars have examined how practitioners operate and how practices unfold, they have yet to connect the specific performativity of each artefact within these processes to its effects. Focusing on practices, the research follows different strands of research. First, it draws on Actor-Network Theory (ANT) and recent ethnographies of architecture. Second, it links such perspective to Problem Structuring Methods (PSMs), focusing on interactions through artefacts. Finally, it contributes to a current debate in organization studies on the role of artefacts as boundary objects. Accordingly, the paper explores the role of architectural design practices in bringing forward effects in the decision-making process of a masterplan for developing an urban university campus. This paper makes a threefold contribution. First, in theoretical terms, tracing the performativity of architectural design practices. Second, in methodological terms, proposing a mapping methodology to trace such practices. Finally, it provides an interactive visualization tool.

本研究探讨了具体的设计文件——作为视觉人工制品——在塑造决策过程中的作用，强调了它们如何在关键时刻通过协商不同的观点来克服冲突。建筑设计研究经历了重大的范式转变，主要是通过传统的社会学和人类学方法到工程和建筑的专业实践。虽然学者们已经研究了实践者是如何操作的以及实践是如何展开的，但他们还没有将这些过程中每个人工制品的具体性能与其效果联系起来。该研究侧重于实践，遵循不同的研究方向。首先，它借鉴了行动者网络理论（ANT）和最近的建筑民族志。其次，它将这种观点与问题结构方法（psm）联系起来，重点关注通过工件的交互。最后，它有助于当前组织研究中关于人工制品作为边界对象的作用的辩论。因此，本文探讨了建筑设计实践在城市大学校园发展总体规划决策过程中的作用。这篇论文有三方面的贡献。首先，在理论方面，追溯建筑设计实践的表演性。其次，在方法论方面，提出了一种追踪此类实践的映射方法。最后，它提供了一个交互式可视化工具。

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引用次数: 0

Preferential knowledge for multi-criteria decision making: Stability and consistency of decision rules and weights 多准则决策的优先知识：决策规则和权重的稳定性和一致性

IF 2.1 Q3 MANAGEMENT

EURO Journal on Decision Processes

Pub Date : 2026-01-01 DOI: 10.1016/j.ejdp.2025.100067

Marko Bohanec , Nikola Kadoić , Nina Begičević Ređep

This research investigates the variability of decision-making preferences, represented in terms of decision rules and criteria weights, in the context of the qualitative multi-criteria method DEX (Decision EXpert). We study the differences between decision rules acquired from different subjects (inter-personal differences) and from the same subjects at different times (intra-personal differences). We also assess the consistency of so-acquired rules and the ability of subjects to estimate the importance (weights) of criteria. The methodological approach consisted of two surveys among students, carried out about one and a half month apart. Four thematic areas were addressed in the questionnaires: selection of study programs, student success, car purchase decisions, and choices regarding everyday shopping venues. In both survey periods, participants were required to assess the importance of these criteria and to define decision rules according to the DEX method. The findings provide insights into the stability of decision-making processes among participants and in time. The results indicate a high variability of decision rules, both inter- and intra-personal. Intra-personal drift is lower than inter-personal differences, but not by much (three-quarters of the latter). The consistency of rules varied between small decision tables with clearly ordered criteria, where it was almost perfect, and large decision tables with less apparent preferential relations. Defining fully consistent decision tables turned out to be hard, indicating the need for automated consistency-checking tools. Criteria weights also drifted in time at the rate about 9% (user-provided weights) and 10–27% (weights assessed algorithmically from decision rules). The main contributions of this study are identified and quantified magnitudes of decision rules variability and consistency.

本研究在定性多准则方法DEX （decision EXpert）的背景下，研究决策偏好的可变性，以决策规则和标准权重表示。我们研究了从不同主体获得的决策规则（人际差异）和从同一主体在不同时间获得的决策规则（个人内差异）之间的差异。我们还评估了所获得规则的一致性以及受试者估计标准重要性（权重）的能力。方法方法包括对学生进行两次调查，间隔大约一个半月。调查问卷涉及四个主题领域：学习计划的选择、学生的成功、购车决定以及日常购物场所的选择。在这两个调查期间，参与者被要求评估这些标准的重要性，并根据DEX方法定义决策规则。这些发现为参与者之间决策过程的稳定性和时间提供了见解。结果表明，决策规则的高度可变性，无论是人与人之间还是人与人之间。个人内部漂移低于个人之间的差异，但相差不多（后者的四分之三）。规则的一致性在具有明确排序标准的小型决策表和具有不太明显的优先关系的大型决策表之间变化，在这些决策表中，规则的一致性几乎是完美的。定义完全一致的决策表是很困难的，这表明需要自动一致性检查工具。标准权重也以9%（用户提供的权重）和10-27%（从决策规则中通过算法评估的权重）的速率随时间漂移。本研究的主要贡献是识别和量化决策规则可变性和一致性的大小。

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引用次数: 0

A stage-gate decision process for guiding the development of AI solutions for preventive maintenance 用于指导预防性维护的人工智能解决方案开发的阶段-门决策过程

IF 2.1 Q3 MANAGEMENT

EURO Journal on Decision Processes

Pub Date : 2025-12-08 DOI: 10.1016/j.ejdp.2025.100063

Jussi Leppinen , Ahti Salo , Michele Compare

The development of Artificial Intelligence (AI) solutions for preventive maintenance applications is a risky and resource-demanding process. Typically, there are several candidate solutions whose performance in transforming data into useful prognostic information is initially uncertain. These uncertainties can be managed by structuring the development process into multiple stages that help choose and implement the final solution. In this paper, we propose such a stage-gate process by using Robust Portfolio Modelling to screen increasingly detailed candidate solutions through four development stages and three decision gates. The development stages generate evidence on how the candidate solutions contribute to six development objectives that represent different financial and technical criteria. At the decision gates, decisions about the continuation/termination of candidate solutions are taken by identifying portfolios of non-dominated candidate solutions subject to time and budget constraints. Uncertainties are captured by admitting incomplete information about the criteria weights and scores of candidate solutions. We illustrate the process by considering the development of an AI solution for a train’s toilet door system. The process brings consistency to the development process and, among other benefits, helps mitigate the risk of missing the development objectives due to premature fixation on a single candidate solution.

开发用于预防性维护应用的人工智能（AI）解决方案是一个有风险且需要资源的过程。通常，有几种候选解决方案，其在将数据转换为有用的预测信息方面的性能最初是不确定的。这些不确定性可以通过将开发过程组织成多个阶段来管理，以帮助选择和实现最终解决方案。在本文中，我们提出了这样一个阶段-门过程，通过使用稳健的投资组合建模筛选越来越详细的候选解决方案，通过四个开发阶段和三个决策门。开发阶段产生关于候选解决方案如何有助于代表不同财务和技术标准的六个开发目标的证据。在决策门，关于候选解决方案的延续/终止的决定是通过确定受时间和预算限制的非主导候选解决方案的组合来做出的。通过承认关于候选解决方案的标准权重和分数的不完整信息来捕获不确定性。我们通过考虑为火车厕所门系统开发人工智能解决方案来说明这一过程。该过程为开发过程带来了一致性，并且在其他好处中，有助于降低由于过早地固定在单个候选解决方案上而错过开发目标的风险。

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引用次数: 0

A Portfolio Selection Model for Planning Natural Gas Smart Energy Hubs with a Multicriteria Benefit-to-Cost Ratio-Based Approach 基于多标准效益成本比方法的天然气智能能源枢纽投资组合选择模型

IF 2.3 Q3 MANAGEMENT

EURO Journal on Decision Processes

Pub Date : 2025-01-01 DOI: 10.1016/j.ejdp.2025.100060

Eduarda Asfora Frej , Carolina Lino Martins , Lucas Borges Leal da Silva , João Batista Sarmento dos Santos Neto , Adiel Teixeira de Almeida

In the context of advancing energy infrastructure, the planning and development of natural gas smart energy hubs have gained importance as essential components of sustainable energy systems. Thus, this paper introduces a portfolio selection model designed to improve the planning process for natural gas smart energy hubs. The proposed model integrates a multicriteria benefit-to-cost ratio-based (BCR) heuristic approach with surrogate weights and swing elicitation procedure, providing a robust framework for decision-makers to assess and prioritize investment options. The methodology encompasses a diverse set of criteria, including economic, environmental, and social factors, ensuring a holistic evaluation of candidate projects. A Decision Support System (DSS) called ROCSPort was proposed to operationalize and validate the proposed methodology, with a view to providing a streamlined preference modeling process for the decision-maker. The DSS also performs a sensitivity analysis based on a Monte-Carlo simulation approach, and statistical tests can be performed to verify the stability of the results. The model’s applicability is demonstrated through a numerical application in a Brazilian energy company, illustrating its capacity to improve the selection of projects based on predefined objectives and constraints. The findings contribute to the energy planning context by offering a systematic and adaptable approach and tool for portfolio selection, aiding decision-makers involved in determining a sustainable energy infrastructure.

在推进能源基础设施建设的背景下，作为可持续能源系统的重要组成部分，天然气智能能源枢纽的规划和发展变得越来越重要。因此，本文引入了一个投资组合选择模型，旨在改进天然气智能能源枢纽的规划过程。该模型将基于多标准效益成本比（BCR）的启发式方法与替代权重和摆动启发程序相结合，为决策者评估和优先考虑投资方案提供了一个强大的框架。该方法包含了一系列不同的标准，包括经济、环境和社会因素，以确保对候选项目进行全面评估。提出了一个名为ROCSPort的决策支持系统（DSS）来实施和验证所建议的方法，以期为决策者提供简化的偏好建模过程。DSS还进行了基于蒙特卡罗模拟方法的灵敏度分析，并可以进行统计测试来验证结果的稳定性。通过在巴西一家能源公司的数值应用证明了该模型的适用性，说明了它能够根据预定义的目标和约束改进项目选择。研究结果为能源规划提供了系统的、适应性强的投资组合选择方法和工具，有助于决策者确定可持续的能源基础设施。

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引用次数: 0

Optimal supply chain design using machine learning, risk assessment and optimisation applied to coal distribution 将机器学习、风险评估和优化应用于煤炭配送的最优供应链设计

IF 2.1 Q3 MANAGEMENT

EURO Journal on Decision Processes

Pub Date : 2025-01-01 DOI: 10.1016/j.ejdp.2025.100062

Spyros Giannelos, Ioannis Konstantelos, Goran Strbac

This paper presents a novel integration of machine learning and optimization techniques for robust supply chain network design under uncertainty, demonstrated through a regional coal distribution system (150 suppliers, 500 consumers, 7.5 million tonnes annually). Unlike traditional approaches that focus solely on cost minimization, our progressive methodology uniquely combines k-means clustering with mixed-integer programming to identify configurations that are both cost-effective and resilient to demand variability. Starting from a baseline single-warehouse configuration costing $404.6 million annually, our approach systematically evaluates multi-facility alternatives through Monte Carlo simulation (50,000 iterations), revealing remarkable system stability—only 0.96 % cost variation despite 25 % individual volume uncertainty. The k-means analysis identifies optimal clustering patterns, while subsequent mixed-integer programming confirms that a five-warehouse configuration reduces annual transportation costs by 45.8 % ($185.3 million savings) while maintaining 90–100 % capacity utilization. This configuration demonstrates a Net Present Value of $3.02 billion over 50 years, significantly outperforming traditional single-facility designs. Critically, correlation analysis reveals that shipment volumes (ρ=0.739) drive costs more than distances (ρ=0.556), challenging conventional distance-minimization paradigms. The integrated framework is computationally efficient (4.2 s to optimality), scalable to larger networks, and applicable to various bulk commodity distribution challenges, offering supply chain managers a robust tool for strategic network design under uncertainty.

本文提出了一种新的机器学习和优化技术的集成，用于不确定性下的稳健供应链网络设计，并通过区域煤炭分配系统（150家供应商，500名消费者，每年750万吨）进行了演示。与只关注成本最小化的传统方法不同，我们的渐进式方法独特地将k均值聚类与混合整数规划相结合，以确定既具有成本效益又能适应需求变化的配置。从每年花费4.046亿美元的基线单仓库配置开始，我们的方法通过蒙特卡罗模拟（50,000次迭代）系统地评估了多设施替代方案，揭示了显着的系统稳定性-尽管25%的个体体积不确定性，但成本变化仅为0.96%。k-means分析确定了最佳聚类模式，而随后的混合整数规划证实，五仓库配置在保持90 - 100%的产能利用率的同时，每年可减少45.8%的运输成本（节省1.853亿美元）。这种配置在50年内的净现值为30.2亿美元，大大优于传统的单一设施设计。至关重要的是，相关分析表明，出货量（ρ=0.739）比距离（ρ=0.556）更能驱动成本，这挑战了传统的距离最小化范式。集成的框架具有计算效率（4.2 s达到最优），可扩展到更大的网络，并适用于各种大宗商品分销挑战，为供应链管理人员提供了不确定情况下战略网络设计的强大工具。

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引用次数: 0

A structured group decision support approach within SMEs under industry 5.0: An application on delivery policy selection 工业5.0下中小企业的结构化群体决策支持方法：交付政策选择的应用

IF 2.1 Q3 MANAGEMENT

EURO Journal on Decision Processes

Pub Date : 2025-01-01 DOI: 10.1016/j.ejdp.2025.100064

Jérémy Traversac , François Galasso , Caroline Thierry , Pascale Zarate

Small and Medium-sized Enterprises (SMEs) have traditionally relied on top-down planning approaches such as Manufacturing Resource Planning II (MRP II), which are increasingly inadequate in addressing the dynamic and uncertain environments shaped by Industry 4.0 and 5.0. These paradigms require organizations to continuously adapt by integrating heterogeneous data, fostering collaboration, and placing humans at the centre of decision-making processes. However, current research on supporting decision-making in SMEs within these contexts remains limited. This paper proposes a structured Group Decision Support System (GDSS) tailored to SMEs, combining a Multi-Criteria Decision-Making (MCDM) approach with a simulation-based planning model. The approach enables actors from different hierarchical levels (strategic, tactical, and operational) to express preferences, compute Key Performance Indicators (KPIs), and collaboratively evaluate alternatives. The approach emphasizes transparency and coherence in decision-making while addressing individual and collective priorities. A didactic case study involving the selection of delivery policies illustrates the applicability and benefits of the proposed approach, allowing users to explore trade-offs, simulate scenarios, and converge towards a shared strategic decision.

传统上，中小型企业（SMEs）依赖于自上而下的规划方法，如制造资源规划II (MRP II)，这在应对工业4.0和5.0形成的动态和不确定环境方面越来越不充分。这些范例要求组织通过集成异构数据、促进协作和将人置于决策过程的中心来不断适应。然而，目前关于中小企业在这些背景下支持决策的研究仍然有限。本文提出了一种适合中小企业的结构化群体决策支持系统（GDSS），该系统将多准则决策（MCDM）方法与基于仿真的规划模型相结合。该方法使来自不同层次（战略、战术和操作）的参与者能够表达偏好、计算关键绩效指标（kpi），并协作评估备选方案。这种方法强调决策的透明度和一致性，同时处理个人和集体的优先事项。涉及交付策略选择的教学案例研究说明了所建议方法的适用性和好处，允许用户探索权衡，模拟场景，并向共享的战略决策靠拢。

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引用次数: 0

Cross-efficiency aggregation method considering bounded rationality: An application to healthcare service 考虑有限理性的交叉效率聚合方法在医疗保健服务中的应用

IF 2.3 Q3 MANAGEMENT

EURO Journal on Decision Processes

Pub Date : 2025-01-01 DOI: 10.1016/j.ejdp.2025.100059

Hao Pan , Guoliang Yang , Yuanyu Lou , Zhongcheng Guan

The cross-efficiency evaluation method is a powerful tool for assessing efficiency. However, previous research has often overlooked the bounded rationality of decision makers (DMs), thereby neglecting key factors. To address this gap, we investigate the cross-efficiency weight aggregation method under bounded rationality. Firstly, we develop a utility function incorporating inequality aversion and overconfidence, integrating them into the cross-efficiency weight aggregation process to formulate the equity-minded cross-efficiency method. Secondly, building upon this method, we address consensus issues within evaluation groups by introducing a consensus compromise algorithm. This algorithm aims to reconcile group opinions based on the principles of the equity-minded cross-efficiency approach. Furthermore, we apply our model to evaluate healthcare service efficiency in China. Our analysis explores the impact of overconfidence and fairness preferences, using a Tobit regression model to examine factors influencing healthcare service efficiency.

交叉效率评价方法是评价效率的有力工具。然而，以往的研究往往忽视了决策者的有限理性，从而忽略了关键因素。为了解决这一问题，我们研究了有限理性下的交叉效率权值聚合方法。首先，我们建立了一个包含不平等厌恶和过度自信的效用函数，并将它们整合到交叉效率权重聚合过程中，形成了公平意识交叉效率方法。其次，在此方法的基础上，我们通过引入共识妥协算法来解决评估组内的共识问题。该算法的目的是基于公平的交叉效率方法的原则来协调群体意见。此外，我们将该模型应用于中国的医疗保健服务效率评估。我们的分析探讨了过度自信和公平偏好的影响，使用Tobit回归模型来检验影响医疗服务效率的因素。

引用次数: 0

Rewarding organisations for sustainable mobility of their employees: A multi-criteria assessment model and certification framework 奖励员工可持续流动的组织：多标准评估模型和认证框架

IF 2.1 Q3 MANAGEMENT

EURO Journal on Decision Processes

Pub Date : 2025-01-01 DOI: 10.1016/j.ejdp.2025.100061

Marko Bohanec , Davor Kontić , Bernard Ženko , Martin Žnidaršič , Karina Sirk , Rok Vodopivec

The concept of sustainable mobility is aimed at minimising environmental impacts of transportation systems while meeting the needs of individuals and communities. This includes encouraging citizens to choose sustainable modes of transportation: walking, cycling, public transport, carpooling, and telecommuting. We present an approach at rewarding organisations that actively support the sustainable mobility of their employees, and propose a framework for awarding a sustainable mobility certificate to organisations that fulfil sustainable mobility goals and objectives. The assessment is carried out using a qualitative rule-based multi-criteria model, which considers 50 indicators. Other elements of the certification process include methods for assessing the mobility structure of employees in the organisation and its potential for improvement. In this paper, we present the main components of the proposed certification framework and illustrate its application for assessing the status of sustainable mobility of employees at a Slovenian research institute.

可持续交通的概念旨在最大限度地减少交通系统对环境的影响，同时满足个人和社区的需求。这包括鼓励市民选择可持续的交通方式：步行、骑自行车、公共交通、拼车和远程办公。我们提出了一种奖励积极支持员工可持续流动性的组织的方法，并提出了一个框架，为实现可持续流动性目标和宗旨的组织颁发可持续流动性证书。评估采用基于规则的定性多标准模型进行，该模型考虑了50个指标。认证过程的其他要素包括评估组织中员工流动结构及其改进潜力的方法。在本文中，我们提出了提出的认证框架的主要组成部分，并说明其在斯洛文尼亚研究机构评估员工可持续流动状况的应用。

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引用次数: 0

Editorial for “Recent advances and applications of multi-objective optimization” 多目标优化的最新进展与应用 "编辑

IF 1 Q3 MANAGEMENT

EURO Journal on Decision Processes

Pub Date : 2024-01-01 DOI: 10.1016/j.ejdp.2024.100049

Gulsah Karakaya , Banu Lokman

引用次数: 0

Understanding tourists’ behavior toward transport mode choice by using machine learning methods 利用机器学习方法了解游客的交通方式选择行为

IF 2.3 Q3 MANAGEMENT

EURO Journal on Decision Processes

Pub Date : 2024-01-01 DOI: 10.1016/j.ejdp.2024.100054

Ali Jamal Mahdi , Domokos Esztergár-Kiss

Recently, transportation problems in evolving cities have become increasingly complex thus requiring innovative solutions. The complexity arises from the combination of urbanization, technological advancements, and diverse demographics. Therefore, integrating advanced methodologies, such as machine learning (ML), into transportation planning becomes essential. This study explores the application of ML techniques to predict and understand tourists’ transport mode choices when engaging in leisure activities. A comparative analysis of various ML algorithms including Neural Networks, k-Nearest Neighbor (k-NN), Naive Bayesian, Decision Tree, Support Vector Machines, Discriminant Analysis, and Ensembles reveals distinctive strengths and trade-offs. Based on the results, Neural Networks demonstrate high accuracy, precision, recall, and specificity, which makes the algorithm well-suited to predict transport mode choices. While k-NN exhibits competitive precision and recall, it struggles with specificity and indicates a higher false positive rate. These findings support transportation planners to select the most suitable algorithm according to the desired outcomes. The adoption of these advanced approaches enhances the understanding of travel behavior thus offering valuable tools for developing efficient urban transportation systems.

近来，不断发展的城市交通问题变得越来越复杂，因此需要创新的解决方案。这种复杂性源于城市化、技术进步和多样化人口结构的结合。因此，将机器学习（ML）等先进方法融入交通规划变得至关重要。本研究探讨了如何应用 ML 技术来预测和了解游客在从事休闲活动时的交通方式选择。通过对神经网络、k-近邻（k-NN）、Naive Bayesian、决策树、支持向量机、判别分析和集合等各种 ML 算法进行比较分析，我们发现了这些算法的独特优势和利弊权衡。根据结果，神经网络表现出较高的准确度、精确度、召回率和特异性，这使得该算法非常适合预测交通模式选择。虽然 k-NN 在精确度和召回率方面具有竞争力，但在特异性方面却很吃力，误报率也较高。这些发现有助于交通规划人员根据预期结果选择最合适的算法。采用这些先进的方法可以加深人们对出行行为的理解，从而为开发高效的城市交通系统提供有价值的工具。

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引用次数: 0