European Journal of Operational Research最新文献_第2页

A coevolutionary algorithm for exploiting a large fuzzy outranking relation

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2024-12-07 DOI: 10.1016/j.ejor.2024.12.012

Jesús Jaime Solano Noriega, Juan Carlos Leyva López, Carlos Andrés Oñate Ochoa, José Rui Figueira

{"title":"A coevolutionary algorithm for exploiting a large fuzzy outranking relation","authors":"Jesús Jaime Solano Noriega, Juan Carlos Leyva López, Carlos Andrés Oñate Ochoa, José Rui Figueira","doi":"10.1016/j.ejor.2024.12.012","DOIUrl":"https://doi.org/10.1016/j.ejor.2024.12.012","url":null,"abstract":"The outranking approach in Multiple Criteria Decision Analysis (MCDA) uses ranking procedures to exploit a fuzzy outranking relation, which captures the decision maker's notion of a ranking. However, as decision problems become more complex and computer performance improves, new ranking procedures are needed to rank complex data sets that decision-makers may not interpret. This paper discusses recent efforts and potential directions for developing ranking procedures that use multiobjective evolutionary algorithms (MOEAs) to exploit a fuzzy outranking relation. After that, based on the cooperative coevolutionary algorithms (CCEA) approach, we suggest some fundamental modifications to extend the RP<ce:sup loc=\"post\">2</ce:sup>-NSGA-II+H algorithm that improve the scalability of this MOEA to exploit large-sized fuzzy outranking relations. Empirical results indicate that adjustments improve the RP<ce:sup loc=\"post\">2</ce:sup>-NSGA-II+H algorithm for the addressed problem. The proposed ranking procedure outperforms RP<ce:sup loc=\"post\">2</ce:sup>-NSGA-II+H in terms of ranking error rates based on the experiments conducted. Our experimental results also demonstrate that the proposed approach can be scaled for instances of the ranking problem of up to one thousand alternatives.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"10 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825211","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}

引用次数: 0

A machine learning approach for solution space reduction in aircraft disruption recovery

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2024-12-06 DOI: 10.1016/j.ejor.2024.11.025

Navid Rashedi, Nolan Sankey, Vikrant Vaze, Keji Wei

{"title":"A machine learning approach for solution space reduction in aircraft disruption recovery","authors":"Navid Rashedi, Nolan Sankey, Vikrant Vaze, Keji Wei","doi":"10.1016/j.ejor.2024.11.025","DOIUrl":"https://doi.org/10.1016/j.ejor.2024.11.025","url":null,"abstract":"Aircraft recovery, a critical step in airline operations recovery, aims to minimize the cost of disrupted aircraft schedules. The exact methods for aircraft recovery are computationally expensive and operationally infeasible in practice. Heuristics and hybrid approaches offer faster solutions but have inconsistent solution quality, often leading to large losses. We propose a supervised machine learning approach to accelerate aircraft recovery by pruning the solution space of the optimization problem. It leverages similarities with previously solved problem instances through an offline model-training phase, identifies components of the optimal solutions for new problem instances in the online phase, and links them to the optimization model to rapidly generate high-quality solutions. Computational results, from multiple historical disruption instances for a large US airline, demonstrate that this approach significantly outperforms exact methods on computational runtime while producing similarly high-quality solutions. It also outperforms existing heuristics due to its ability to prune solution spaces in a more principled manner, leading to higher quality solutions in similarly short runtimes. For a runtime budget of two minutes, our approach provides a solution within 1.5% of the true optimal cost, resulting in an average daily saving of over $390,000 compared to all existing approaches. The main drivers of these improvements are explainable in terms of key airline operational metrics and are validated through extensive sensitivity and robustness tests.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"200 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825217","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}

引用次数: 0

Optimal fulfillment and replenishment for omnichannel retailers with standard shipping contracts

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2024-12-06 DOI: 10.1016/j.ejor.2024.11.051

Bartu Arslan, Albert H. Schrotenboer, Zümbül Atan

{"title":"Optimal fulfillment and replenishment for omnichannel retailers with standard shipping contracts","authors":"Bartu Arslan, Albert H. Schrotenboer, Zümbül Atan","doi":"10.1016/j.ejor.2024.11.051","DOIUrl":"https://doi.org/10.1016/j.ejor.2024.11.051","url":null,"abstract":"E-commerce sales rise exponentially and represent an increasing proportion of global retail. To benefit from this, traditional brick-and-mortar stores enter the e-commerce market and become omnichannel retailers. However, the profitability of omnichannel retailers remains questionable due to high shipment and fulfillment costs. This paper addresses this challenge, focusing on using standard shipping contracts as a potential solution. Such contracts promise delivery within a given number of periods. Once a customer orders, the retailer should set a delivery period. In this way, retailers are flexible in setting exact delivery days, providing an opportunity for jointly optimizing product replenishment and customer fulfillment. We provide a generic model for the use of standard shipping contracts and formulate it as a Markov decision process. We provide optimal solutions using a modified policy iteration algorithm. Our results show that using standard shipping contracts creates a win-win situation: It increases profits and customer service. The observed profit increase is directly linked to maintaining less on-hand inventory. This effect is more pronounced for higher valued products and longer replenishment lead times. Additionally, we propose a heuristic policy that performs within 4% of the optimal policy.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"3 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825213","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}

引用次数: 0

Flexible enhanced indexation models through stochastic dominance and ordered weighted average optimization

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2024-12-05 DOI: 10.1016/j.ejor.2024.11.050

Francesco Cesarone, Justo Puerto

{"title":"Flexible enhanced indexation models through stochastic dominance and ordered weighted average optimization","authors":"Francesco Cesarone, Justo Puerto","doi":"10.1016/j.ejor.2024.11.050","DOIUrl":"https://doi.org/10.1016/j.ejor.2024.11.050","url":null,"abstract":"In this paper, we discuss portfolio selection strategies for Enhanced Indexation (EI), which are based on stochastic dominance relations. The goal is to select portfolios that stochastically dominate a given benchmark but that, at the same time, must generate some excess return with respect to a benchmark index. To achieve this goal, we propose a new methodology that selects portfolios using the ordered weighted average (OWA) operator, which generalizes previous approaches based on minimax selection rules and still leads to solving linear programming models. We also introduce a new type of approximate stochastic dominance rule and show that it implies the almost Second-order Stochastic Dominance (SSD) criterion proposed by Lizyayev and Ruszczyński (2012). We prove that our EI model based on OWA selects portfolios that dominate a given benchmark through this new form of stochastic dominance criterion. We test the performance of the obtained portfolios in an extensive empirical analysis based on real-world datasets. The computational results show that our proposed approach outperforms several SSD-based strategies widely used in the literature, as well as the global minimum variance portfolio.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"250 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825226","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}

引用次数: 0

An incremental preference elicitation-based approach to learning potentially non-monotonic preferences in multi-criteria sorting

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2024-12-05 DOI: 10.1016/j.ejor.2024.11.047

Zhuolin Li, Zhen Zhang, Witold Pedrycz

{"title":"An incremental preference elicitation-based approach to learning potentially non-monotonic preferences in multi-criteria sorting","authors":"Zhuolin Li, Zhen Zhang, Witold Pedrycz","doi":"10.1016/j.ejor.2024.11.047","DOIUrl":"https://doi.org/10.1016/j.ejor.2024.11.047","url":null,"abstract":"Leveraging assignment example preference information, to determine the shape of marginal utility functions and category thresholds of the threshold-based multi-criteria sorting (MCS) model, has emerged as a focal point of current research within the realm of MCS. Most studies assume decision makers can provide all assignment example preference information in batch and that their preferences over criteria are monotonic, which may not align with practical MCS problems. This paper introduces a novel incremental preference elicitation-based approach to learning potentially non-monotonic preferences in MCS problems, enabling decision makers to progressively provide assignment example preference information. Specifically, we first construct a max-margin optimization-based model to model potentially non-monotonic preferences and inconsistent assignment example preference information in each iteration of the incremental preference elicitation process. Using the optimal objective function value of the max-margin optimization-based model, we devise information amount measurement methods and question selection strategies to pinpoint the most informative alternative in each iteration within the framework of uncertainty sampling in active learning. Once the termination criterion is satisfied, the sorting result for non-reference alternatives can be determined through the use of two optimization models, i.e., the max-margin optimization-based model and the complexity controlling optimization model. Subsequently, two incremental preference elicitation-based algorithms are developed to learn potentially non-monotonic preferences, considering different termination criteria. Ultimately, we apply the proposed approach to a firm financial state rating problem to elucidate the detailed implementation steps, and perform computational experiments on both artificial and real-world data sets to compare the proposed question selection strategies with several benchmark strategies.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"282 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142874820","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}

引用次数: 0

Information sharing across competing platforms with varying information capabilities

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2024-12-04 DOI: 10.1016/j.ejor.2024.11.048

Haoruo Zhu, Yaodong Ni, Yongbo Xiao

{"title":"Information sharing across competing platforms with varying information capabilities","authors":"Haoruo Zhu, Yaodong Ni, Yongbo Xiao","doi":"10.1016/j.ejor.2024.11.048","DOIUrl":"https://doi.org/10.1016/j.ejor.2024.11.048","url":null,"abstract":"Competing online retail platforms frequently function as both agency and reselling channels. This paper explores a manufacturer’s channel selection strategy in the context of downstream platform competition and information sharing, taking into account the platforms’ varying levels of information capability. Our research indicates that the manufacturer opts for a hybrid channel approach. Competing platforms aim to be selected as agency channels by offering information sharing and reduced commission fees. Interestingly, the manufacturer chooses the platform with lesser information capability as her agency channel to gain access to shared demand data, while opting for the platform with greater capability as reselling channel without accessing his demand data. The platform with inferior information capability is more inclined to establish a revenue-sharing partnership with the manufacturer to mitigate risks, leading him to decrease his commission rate to attract the manufacturer to select him as the agency channel. We demonstrate that, under conditions of demand uncertainty, a significant distinction between agency and reselling channels lies in the distribution of risk, i.e., whether the platform assumes the risk alone or shares it with the manufacturer. Furthermore, we highlight the <ce:italic>free-ride effect</ce:italic>, wherein an agency platform can benefit from his rival’s superior information capability. As a result, a complex relationship, characterized by both cooperation and rivalry, may develop between the two platforms.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"19 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825224","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}

引用次数: 0

Multi-label feature selection considering label importance-weighted relevance and label-dependency redundancy

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2024-12-04 DOI: 10.1016/j.ejor.2024.11.038

Xi-Ao Ma, Haibo Liu, Yi Liu, Justin Zuopeng Zhang

{"title":"Multi-label feature selection considering label importance-weighted relevance and label-dependency redundancy","authors":"Xi-Ao Ma, Haibo Liu, Yi Liu, Justin Zuopeng Zhang","doi":"10.1016/j.ejor.2024.11.038","DOIUrl":"https://doi.org/10.1016/j.ejor.2024.11.038","url":null,"abstract":"Information theory has emerged as a prominent approach for analyzing feature relevance and redundancy in multi-label feature selection. However, traditional information theory-based methods encounter two primary issues. Firstly, when evaluating feature relevance, they fail to consider the differing importance of each label within the entire label set. Secondly, when assessing feature redundancy, they overlook the varying dependencies of the selected features on the labels. To address these issues, this paper proposes a novel multi-label feature selection method that considers label importance-weighted relevance and label-dependency redundancy. Specifically, we introduce the concept of label importance weight (LIW) to measure the significance of each label within the entire label set. Based on this LIW, we define a feature relevance term called label importance-weighted relevance (LIWR). Subsequently, we leverage the uncertainty coefficient to quantify the dependence of the selected features on the labels, treating it as a weight. Building upon this weight, we establish a feature redundancy term known as label-dependency redundancy (LDR). Finally, we formulate a feature evaluation criterion called LIWR-LDR by maximizing LIWR and minimizing LDR, accompanied by the presentation of a corresponding feature selection algorithm. Extensive experiments conducted on 25 multi-label datasets demonstrate the effectiveness of LIWR-LDR.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"43 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825222","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}

引用次数: 0

Stochastic scheduling and routing decisions in online meal delivery platforms with mixed force

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2024-12-04 DOI: 10.1016/j.ejor.2024.11.028

Yanlu Zhao, Laurent Alfandari, Claudia Archetti

{"title":"Stochastic scheduling and routing decisions in online meal delivery platforms with mixed force","authors":"Yanlu Zhao, Laurent Alfandari, Claudia Archetti","doi":"10.1016/j.ejor.2024.11.028","DOIUrl":"https://doi.org/10.1016/j.ejor.2024.11.028","url":null,"abstract":"This paper investigates stochastic scheduling and routing problems in the online meal delivery (OMD) service. The huge increase in meal delivery demand requires the service providers to construct a highly efficient logistics network to deal with a large-volume of time-sensitive and fluctuating fulfillment, often using inhouse and crowdsourced drivers to secure the ambitious service quality. We aim to address the problem of developing an effective scheduling and routing policy that can handle real-life situations. To this end, we first model the dynamic problem as a Markov Decision Process (MDP) and analyze the structural properties of the optimal policy. Then we propose four integrated approaches to solve the operational level scheduling and routing problem. In addition, we provide a continuous approximation formula to estimate the bounds of required fleet size for the inhouse drivers. Numerical experiments based on a real dataset show the effectiveness of the proposed solution approaches. We also obtain several managerial insights that can help decision makers in solving similar resource allocation problems in real-time.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"21 12 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825218","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}

引用次数: 0

Optimal computation budget allocation with Gaussian process regression 利用高斯过程回归优化计算预算分配

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2024-12-04 DOI: 10.1016/j.ejor.2024.11.049

Mingjie Hu, Jie Xu, Chun-Hung Chen, Jian-Qiang Hu

引用次数: 0

The location routing problem with time windows and load-dependent travel times for cargo bikes

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2024-12-03 DOI: 10.1016/j.ejor.2024.11.040

Alexander Rave, Pirmin Fontaine

引用次数: 0