European Journal of Operational Research最新文献

{"title":"Managing supply chains facing extreme weather: Supplier’s nature and investment","authors":"Indranil Biswas, Dewang Pagare, Sunil Tiwari, Tsan-Ming Choi","doi":"10.1016/j.ejor.2025.02.026","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.02.026","url":null,"abstract":"In recent times, extreme weather conditions have been playing havoc on supply chains. Companies are investing in climate-specific assets to mitigate weather-related risks and ensure continuous supply chain activities. In this paper, we analytically investigate a supplier’s decision regarding climate-specific investment to understand how the probability of weather disruption, its effort during extreme weather, and its reciprocal behavior influence the buyer’s optimal order decision. We develop a dynamic game model to capture and examine the nature of the supplier–buyer interaction. We also investigate the impact of the supplier’s nature on this interaction during an extreme weather event. Our key findings are as follows: (i) With a higher probability of extreme weather disruption, the supplier prefers generic investment over climate-specific investment. (ii) With a decrease in the probability of extreme weather events, the non-proactive supplier prefers generic investment, whereas the proactive supplier prefers climate-specific investment. This situation allows proactive suppliers to reveal themselves and buyers to recognize the nature of suppliers by observing their investment type. The buyer chooses to source from the proactive supplier when it anticipates extreme weather scenarios. (iii) A downstream buyer orders less from the non-proactive supplier and orders the required quantity from the proactive supplier. There exists a pooling equilibrium for the supplier–buyer interaction where all types of suppliers choose a climate-specific investment, and the buyer orders its required order quantity. Subsequently, through extended analysis, we demonstrate that the proactive supplier charges a higher per-unit price to the buyer in the case of a higher possibility of extreme weather events. The proactive supplier charges a reduced per-unit price only if it exhibits reciprocal behavior. From our analysis, we also find that, with an increase in the cost of climate-specific investment, a non-proactive supplier tends to choose a generic investment and a proactive supplier tends to choose a climate-specific investment.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"17 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Speeding up Grover’s algorithm","authors":"Stefan Creemers","doi":"10.1016/j.ejor.2025.02.034","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.02.034","url":null,"abstract":"To find one of the <mml:math altimg=\"si338.svg\" display=\"inline\"><mml:mi>M</mml:mi></mml:math> target entries in an unstructured database that has <mml:math altimg=\"si337.svg\" display=\"inline\"><mml:mi>N</mml:mi></mml:math> entries, Grover’s algorithm performs <mml:math altimg=\"si3.svg\" display=\"inline\"><mml:mrow><mml:mfrac bevelled=\"true\"><mml:mrow><mml:mi>π</mml:mi></mml:mrow><mml:mrow><mml:mn>4</mml:mn></mml:mrow></mml:mfrac><mml:msqrt><mml:mrow><mml:mfrac bevelled=\"true\"><mml:mrow><mml:mi>N</mml:mi></mml:mrow><mml:mrow><mml:mi>M</mml:mi></mml:mrow></mml:mfrac></mml:mrow></mml:msqrt></mml:mrow></mml:math> iterations. In each iteration, a function is called that evaluates whether an entry is a target entry. Compared to a classical procedure, that requires <mml:math altimg=\"si339.svg\" display=\"inline\"><mml:mfrac bevelled=\"true\"><mml:mrow><mml:mi>N</mml:mi></mml:mrow><mml:mrow><mml:mi>M</mml:mi></mml:mrow></mml:mfrac></mml:math> evaluations, Grover’s algorithm achieves a quadratic speedup. This quadratic speedup, combined with its general applicability as a search algorithm, have made Grover’s algorithms one of the most important (quantum) algorithms available today. A study to improve its runtime is more than justified. For this purpose, we investigate two speedup strategies: (1) reducing the number of iterations that are performed in each run of Grover’s algorithm and (2) partitioning the database. For each of these strategies, we not only execute Grover’s algorithm in parallel, but also explore the possibility to execute Grover’s algorithm in series on a single Quantum Processing Unit (QPU) as well as on multiple QPUs. For each combination of execution mode (serial, parallel, and serial/parallel) and speedup strategy, we show how to obtain optimal policies using closed-form expressions and a gradient-descent procedure. For a single QPU we obtain a speedup factor of 1.1382 when compared to a textbook implementation of Grover’s algorithm. If multiple QPUs are at our disposal, we obtain a speedup factor of at most <mml:math altimg=\"si5.svg\" display=\"inline\"><mml:mrow><mml:mn>1</mml:mn><mml:mo>.</mml:mo><mml:mn>1382</mml:mn><mml:msqrt><mml:mrow><mml:mi>Q</mml:mi></mml:mrow></mml:msqrt></mml:mrow></mml:math>, where <mml:math altimg=\"si279.svg\" display=\"inline\"><mml:mi>Q</mml:mi></mml:math> denotes the number of QPUs. In addition, we show that the dominant policies that minimize the expected number of Grover iterations also minimize the expected number of iterations that are performed per qubit.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"9 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143641013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mathematical models and heuristics for double-load crane scheduling in slab yards","authors":"Zixiong Dong, Ada Che, Jianguang Feng","doi":"10.1016/j.ejor.2025.02.036","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.02.036","url":null,"abstract":"This paper studies a novel crane scheduling problem with unconstrained double-load operations (CSP-UDL) in slab yards. It aims to optimize the sequence of crane operations to minimize makespan. Unlike conventional crane operations, which handle one or two slabs per trip, the unconstrained double-load operation enables the transport of more than two slabs in a single trip, thereby improving logistic efficiency and reducing the makespan. To tackle this problem, we propose two mixed integer linear programming (MILP) models for solving small- and medium-sized instances. We develop two heuristics for large-sized instances: a hybrid heuristic and a matheuristic. The hybrid heuristic integrates tabu search within an adaptive large neighborhood search (ALNS) framework, while the matheuristic integrates this hybrid heuristic with an MILP model, leveraging the strengths of both exact and heuristic methods. Extensive computational experiments demonstrate that while the proposed MILP models can exactly solve instances with up to 50 tasks, the hybrid heuristic and the matheuristic demonstrate robust performance in solving large-sized instances.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"24 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143640994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stow & pick: Optimizing combined stowing and picking tours in scattered storage warehouses","authors":"Stefan Bock, Nils Boysen","doi":"10.1016/j.ejor.2025.02.037","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.02.037","url":null,"abstract":"To streamline order fulfillment, many e-commerce retailers apply scattered storage in their picker-to-parts warehouses. Instead of putting homogeneous unit loads into racks, they break up the pallets and store individual products within mixed shelves. This increases the probability that (somewhere in the vast warehouses) products, ending up jointly on hardly predictable pick lists, can be picked from neighboring shelves. Scattered storage promises a reduction of picker travel but comes at the price of additional stowing effort. Instead of applying separate workforces, stowing and picking can also be combined. This paper provides an exact routing algorithm for a worker with a picking cart who departs from the depot with multiple bins filled with products to stow, switches to picking underway, and returns bins full of picked products to the depot. We identify nine different combined stowing and picking policies. We provide an exact solution procedure based on the branch&amp;bound paradigm for all these policies, based on the parallel-aisle structure of warehouses. If a constant limits the number of relevant regions (i.e., picking aisle subsections between adjacent cross aisles with a storage position to be visited), this algorithm guarantees polynomial runtime. We apply our algorithm to benchmark the gains of the nine combined stowing and picking policies compared to the traditional approach, where stowing and picking are executed by separate workforces. Depending on the selected policy, average gains between 11.8 and 42.0 % arise.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"13 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143641012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The three-way decision model and multi-attribute decision-making: Methodological traps and challenges","authors":"Decui Liang,&nbsp;Chenglong Yang","doi":"10.1016/j.ejor.2025.02.035","DOIUrl":"10.1016/j.ejor.2025.02.035","url":null,"abstract":"<div><div>The three-way decision (3WD) model has lately gained a lot of attention in data analysis and decision-making, and has even become a methodological framework that brings new insights into old problems. Our research is inspired by Bisht and Pal (2024) who introduced an innovative 3WD model which frames multi-attribute decision-making (MADM) problems. Considering both the loss and utility associated with various alternatives, they deduced the threshold values and directly integrated them to determine the final thresholds of 3WD. However, this approach does not fully address the precondition of the minimum expected cost or the maximum expected return inherent in the Bayesian decision procedure. In this paper, we would like to fill this research gap and discuss methodological aspects of establishing the decision thresholds of the 3WD model. Specifically, the experimental analysis demonstrates that the decision results generated by the decision model of Bisht and Pal (2024) may be inconsistent with the optimal decision results derived from the maximum expected return, thus potentially leading to conflicting outcomes. In the present paper, we address this problem and deduce more optimal expressions for the thresholds on the basis of the Bayesian decision procedure. In addition, through comparative experimental analysis, the rationality and effectiveness of the proposed threshold calculation method are verified. Finally, in the concrete derivation process, we also reveal the criteria for the existence of two-way decision, which makes our model applicable to more general situations.</div></div>","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"324 1","pages":"Pages 351-360"},"PeriodicalIF":6.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Robust Bike sharing Rebalancing Problem: Formulations and a branch-and-cut algorithm","authors":"Bruno P. Bruck, Walton P. Coutinho, Pedro Munari","doi":"10.1016/j.ejor.2025.02.029","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.02.029","url":null,"abstract":"Bike Sharing Systems (BSSs) offer a sustainable and efficient urban transportation solution, bringing flexible and eco-friendly alternatives to city logistics. During their operation, BSSs may suffer from unbalanced bike distribution among stations, requiring rebalancing operations throughout the system. The inherent uncertain demand at the stations further complicates these rebalancing operations, even when performed during downtime. This paper addresses this challenge by introducing the Robust Bike Sharing Rebalancing Problem (RBRP), which relies on Robust Optimization techniques to promote better decisions in rebalancing operations in BSSs. Very few studies have considered uncertainty in this context, despite it being a common characteristic with a significant impact on the performance of the system. We present two new formulations and a tailored branch-and-cut algorithm for the RBRP. The first formulation is compact and based on the linearization of recursive equations, while the second is based on robust rounded capacity inequalities and feasibility cuts. Computational results based on benchmark instances indicate the effectiveness of our approaches to face uncertain demand in rebalancing operations and highlight the benefits of using robust solutions to support decision-making in this context.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"86 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143641019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[formula omitted]-Tree: Crossing sharp boundaries in regression trees to find neighbors","authors":"Xuecheng Tian, Shuaian Wang, Lu Zhen, Zuo-Jun (Max) Shen","doi":"10.1016/j.ejor.2025.02.031","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.02.031","url":null,"abstract":"Traditional classification and regression trees (CARTs) utilize a top-down, greedy approach to split the feature space into sharply defined, axis-aligned sub-regions (leaves). Each leaf treats all of the samples therein uniformly during the prediction process, leading to a constant predictor. Although this approach is well known for its interpretability and efficiency, it overlooks the complex local distributions within and across leaves. As the number of features increases, this limitation becomes more pronounced, often resulting in a concentration of samples near the boundaries of the leaves. Such clustering suggests that there is potential in identifying closer neighbors in adjacent leaves, a phenomenon that is unexplored in the literature. Our study addresses this gap by introducing the <mml:math altimg=\"si545.svg\" display=\"inline\"><mml:mi>k</mml:mi></mml:math>-Tree methodology, a novel method that extends the search for nearest neighbors beyond a single leaf to include adjacent leaves. This approach has two key innovations: (1) establishing an adjacency relationship between leaves across the tree space and (2) designing novel intra-leaf and inter-leaf distance metrics through an optimization lens, which are tailored to local data distributions within the tree. We explore three implementations of the <mml:math altimg=\"si545.svg\" display=\"inline\"><mml:mi>k</mml:mi></mml:math>-Tree methodology: (1) the Post-hoc <mml:math altimg=\"si545.svg\" display=\"inline\"><mml:mi>k</mml:mi></mml:math>-Tree (P<mml:math altimg=\"si545.svg\" display=\"inline\"><mml:mi>k</mml:mi></mml:math>-Tree), which integrates the <mml:math altimg=\"si545.svg\" display=\"inline\"><mml:mi>k</mml:mi></mml:math>-Tree methodology into constructed decision trees, (2) the Advanced <mml:math altimg=\"si545.svg\" display=\"inline\"><mml:mi>k</mml:mi></mml:math>-Tree, which seamlessly incorporates the <mml:math altimg=\"si545.svg\" display=\"inline\"><mml:mi>k</mml:mi></mml:math>-Tree methodology during the tree construction process, and (3) the P<mml:math altimg=\"si545.svg\" display=\"inline\"><mml:mi>k</mml:mi></mml:math>-random forest, which integrates the P<mml:math altimg=\"si545.svg\" display=\"inline\"><mml:mi>k</mml:mi></mml:math>-Tree principles with the random forest framework. The results of empirical evaluations conducted on a variety of real-world and synthetic datasets demonstrate that the <mml:math altimg=\"si545.svg\" display=\"inline\"><mml:mi>k</mml:mi></mml:math>-Tree methods have greater prediction accuracy over the traditional models. These results highlight the potential of the <mml:math altimg=\"si545.svg\" display=\"inline\"><mml:mi>k</mml:mi></mml:math>-Tree methodology in enhancing predictive analytics by providing a deeper insight into the relationships between samples within the tree space.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"110 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patient-to-room assignment with single-rooms entitlements: Combinatorial insights and integer programming formulations","authors":"Tabea Brandt, Christina Büsing, Felix Engelhardt","doi":"10.1016/j.ejor.2025.02.018","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.02.018","url":null,"abstract":"Patient-to-room assignment (PRA) is a scheduling problem in decision support for hospitals. It consists of assigning patients to rooms during their stay at a hospital according to certain conditions and objectives, e.g., ensuring gender separated rooms, avoiding transfers and respecting single-room requests. This work presents combinatorial insights about the feasibility of PRA and about how (many) single-room requests can be respected. We further compare different integer programming (IP) formulations for PRA as well as the influence of different objectives on the runtime using real-world data. Based on these results, we develop a fast IP-based solution approach, which obtains high quality solutions. In contrast to previous IP-formulations, the results of our computational study indicate that large, real-world instances can be solved to a high degree of optimality within (fractions of) seconds. We support this result by a computational study using a large set of realistic but randomly generated instances with 50% to 95% capacity utilisation.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"125 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143641018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptation, comparison and practical implementation of fairness schemes in Kidney Exchange Programs","authors":"William St-Arnaud, Margarida Carvalho, Golnoosh Farnadi","doi":"10.1016/j.ejor.2025.02.014","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.02.014","url":null,"abstract":"Kidney Exchange Programs (KEPs) typically maximize overall patient benefit through donor exchanges. This aggregation of benefits (utilitarian objective) calls into question potential individual patient disparities in terms of access to transplantation in KEPs. Moreover, current KEP policies are all-or-nothing, meaning that only one exchange plan is determined — each patient is either selected or not as part of that unique solution. In this work, we extend the space of policies by seeking a lottery over the set of exchange plans that contemplates the (ex-ante) probability of patients being in a solution. To guide the determination of our policy, we adapt popular fairness schemes to KEPs to balance the usual approach of maximizing the utilitarian objective. Different combinations of fairness and utilitarian objectives are modeled as conic programs with an exponential number of variables. We propose a column generation approach to solve them effectively in practice. Finally, we make an extensive comparison of the different schemes in terms of the balance of utility and fairness score, and validate the scalability of our methodology for benchmark instances from the literature.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"26 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lagrangian relaxation and branch-and-price algorithm for resource assignment problem in divisional seru systems","authors":"Shiming Chen, Chengkuan Zeng, Yu Zhang, Jiafu Tang, Chongjun Yan","doi":"10.1016/j.ejor.2025.02.038","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.02.038","url":null,"abstract":"This paper addresses seru formation problem in divisional seru production system (SPS), which focuses on job-seru assignment, worker-seru assignment and operation-worker assignment in each seru. The problem is formulated as a mixed-integer nonlinear programming (MINLP) model with the objective of minimizing training and processing costs of workers. Once the job-seru assignment is determined, we employ a mixed-integer linear programming (MILP) model to describe worker-seru and operation-worker assignment in each seru. To tackle this challenge, we propose a two-phase approach to deal with this problem. In the first phase, we propose a Lagrangian relaxation algorithm to determine job-seru assignment, this approach can quickly compute the lower bound of the MILP by enumerating all possible job-seru assignments and eliminate unpromising ones. Subsequently, in the second phase, for each remaining job-seru assignment, we develop a branch-and-price algorithm to solve the MILP exactly. It is in the branch-and-bound framework, each node is solved by column generation (CG) algorithm. In CG, we apply a Dantzig Wolfe decompose to divide the original problem into a master problem and the pricing problems. A novel label-setting algorithm is employed based on the characteristics of the pricing problem. Additionally, we introduce effective acceleration strategies such as dominance rules and heuristic pricing. It facilitates the selection of the optimal job-seru assignment and obtains the optimal solution for the entire problem. Finally, extensive experiments validate the effectiveness and superiority of our proposed algorithm. We also discuss the impact of selected parameters on the cost and offer managerial insights.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"33 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143641014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}