Operations Research Perspectives最新文献

{"title":"Research on green supply chain finance risk identification based on two-stage deep learning","authors":"Ying Liu ,&nbsp;Sizhe Li ,&nbsp;Chunmei Yu ,&nbsp;Mingli Lv","doi":"10.1016/j.orp.2024.100311","DOIUrl":"10.1016/j.orp.2024.100311","url":null,"abstract":"<div><p>As a resonance product between financial services and the upgrading of the green industry, green supply chain finance has garnered extensive attention in the process of ecological civilization construction. Effectively promoting the green transformation of small and medium-sized enterprises and achieving the \"dual carbon\" goals necessitate the avoidance of corporate green risks. However, the complex interdependence and information asymmetry among green supply chain finance enterprises result in data characteristics such as multi-source small samples and high-dimensional imbalance. To address these issues, this paper proposes a risk assessment model based on two-stage deep learning. In the first stage, we employ Generative Adversarial Network (GAN) to generate minority class default samples, and utilize Stacked Auto-Encoder (SAE) to extract data features with closed-form parameter calculation capability. In the second stage, the obtained features are input into a Deep Neural Network (DNN), and parameter learning and model optimization are conducted through joint training. Finally, to model low-order feature interactions, we integrate the Support Vector Machine (SVM) algorithm. The paper is grounded in the green innovation production of enterprises, collecting financial data of 176 upstream and downstream enterprises and corresponding core enterprise green indicators from 2013 to 2022. Experimental results demonstrate that GAN oversampling technique not only enhances the model's AUC metric but also significantly improves the F1 score. Compared with traditional deep learning methods, the proposed two-stage deep integration model effectively reduces training loss and exhibits superiority in identifying green supply chain finance risks.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"13 ","pages":"Article 100311"},"PeriodicalIF":3.7,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214716024000150/pdfft?md5=970d26bdb80bf86f740ed999ad2ea4a2&pid=1-s2.0-S2214716024000150-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141845423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated machine learning methodology for optimizing production processes in small and medium-sized enterprises","authors":"Yarens J. Cruz ,&nbsp;Alberto Villalonga ,&nbsp;Fernando Castaño ,&nbsp;Marcelino Rivas ,&nbsp;Rodolfo E. Haber","doi":"10.1016/j.orp.2024.100308","DOIUrl":"https://doi.org/10.1016/j.orp.2024.100308","url":null,"abstract":"<div><p>Machine learning can be effectively used to generate models capable of representing the dynamic of production processes of small and medium-sized enterprises. These models enable the estimation of key performance indicators, and are often used for optimizing production processes. However, in most industrial applications, modeling and optimization of production processes are currently carried out as separate tasks, manually in a very costly and inefficient way. Automated machine learning tools and frameworks facilitate the path for deriving models, reducing modeling time and cost. However, optimization by exploiting production models is still in infancy. This work presents a methodology for integrating a fully automated procedure that embraces automated machine learning pipelines and a multi-objective optimization algorithm for improving the production processes, with special focus on small and medium-sized enterprises. This procedure is supported on embedding the generated models as objective functions of a reference point based non-dominated sorting genetic algorithm, resulting in preference-based Pareto-optimal parametrizations of the corresponding production processes. The methodology was implemented and validated using data from a manufacturing production process of a small manufacturing enterprise, generating highly accurate machine learning-based models for the analyzed indicators. Additionally, by applying the optimization step of the proposed methodology it was possible to increase the productivity of the manufacturing process by 3.19 % and reduce its defect rate by 2.15 %, outperforming the results obtained with traditional trial and error method focused on productivity alone.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"12 ","pages":"Article 100308"},"PeriodicalIF":2.5,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214716024000125/pdfft?md5=85cdd1f40a19c1e0b701cd06bd056884&pid=1-s2.0-S2214716024000125-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141324592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ESG integration in portfolio selection: A robust preference-based multicriteria approach","authors":"Ana Garcia-Bernabeu ,&nbsp;Adolfo Hilario-Caballero ,&nbsp;Fabio Tardella ,&nbsp;David Pla-Santamaria","doi":"10.1016/j.orp.2024.100305","DOIUrl":"10.1016/j.orp.2024.100305","url":null,"abstract":"<div><p>We present a framework for multi-objective optimization where the classical mean–variance portfolio model is extended to integrate the environmental, social and governance (ESG) criteria on the same playing field as risk and return and, at the same time, to reflect the investors’ preferences in the optimal portfolio allocation. To obtain the three–dimensional Pareto front, we apply an efficient multi-objective genetic algorithm, which is based on the concept of <span><math><mi>ɛ</mi></math></span>-dominance. We next address the issue of how to incorporate investors’ preferences to express the relative importance of each objective through a robust weighting scheme in a multicriteria ranking framework. The new proposal has been applied to real data to find optimal portfolios of socially responsible investment funds, and the main conclusion from the empirical tests is that it is possible to provide the investors with a robust solution in the mean–variance–ESG surface according to their preferences.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"12 ","pages":"Article 100305"},"PeriodicalIF":2.5,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214716024000095/pdfft?md5=844c952d89a5e3cb430a5a472d124362&pid=1-s2.0-S2214716024000095-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141135964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ranking-based second stage in data envelopment analysis: An application to research efficiency in higher education","authors":"Vladimír Holý","doi":"10.1016/j.orp.2024.100306","DOIUrl":"https://doi.org/10.1016/j.orp.2024.100306","url":null,"abstract":"<div><p>An alternative approach for the panel second stage of data envelopment analysis (DEA) is presented in this paper. Instead of efficiency scores, we propose to model rankings in the second stage using a dynamic ranking model in the score-driven framework. We argue that this approach is suitable to complement traditional panel regression as a robustness check. To demonstrate the proposed approach, we determine research efficiency of higher education systems at country level by examining scientific publications and analyze its relation to good governance. The proposed approach confirms positive relation to the Voice and Accountability indicator, as found by the standard panel linear regression, while suggesting caution regarding the Government Effectiveness indicator.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"12 ","pages":"Article 100306"},"PeriodicalIF":2.5,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214716024000101/pdfft?md5=66019cddd01de1f60ad172644fb678e1&pid=1-s2.0-S2214716024000101-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141243171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chance constrained directional models in stochastic data envelopment analysis","authors":"V.J. Bolós ,&nbsp;R. Benítez ,&nbsp;V. Coll-Serrano","doi":"10.1016/j.orp.2024.100307","DOIUrl":"10.1016/j.orp.2024.100307","url":null,"abstract":"<div><p>We construct a new family of chance constrained directional models in stochastic data envelopment analysis, generalizing the deterministic directional models and the chance constrained radial models. We prove that chance constrained directional models define the same concept of stochastic efficiency as the one given by chance constrained radial models and, as a particular case, we obtain a stochastic version of the generalized Farrell measure. Finally, we give some examples of application of chance constrained directional models with stochastic and deterministic directions, showing that inefficiency scores obtained with stochastic directions are less or equal than those obtained considering deterministic directions whose values are the means of the stochastic ones.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"12 ","pages":"Article 100307"},"PeriodicalIF":2.5,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214716024000113/pdfft?md5=b203f1d3524e063c3af56ce9551bd228&pid=1-s2.0-S2214716024000113-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141407217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective optimization for perishable product dispatch in a FEFO system for a food bank single warehouse","authors":"Carlos Aníbal Suárez ,&nbsp;Walter A. Guaño ,&nbsp;Cinthia C. Pérez ,&nbsp;Heydi Roa-López","doi":"10.1016/j.orp.2024.100304","DOIUrl":"https://doi.org/10.1016/j.orp.2024.100304","url":null,"abstract":"<div><p>One of the main challenges of food bank warehouses in developing countries is to determine how to allocate perishable products to beneficiary agencies with different expiry dates while ensuring food safety, meeting nutritional requirements, and minimizing the shortage. The contribution of this research is to introduce a new multi-objective, multi-product, and multi-period perishable food allocation problem based on a single warehouse management system for a First Expired-First Out (FEFO) policy. Moreover, it incorporates the temporal aspect, guaranteeing the dispatch of only those perishable products that meet the prescribed minimum quality standards. A weighted sum approach converts the multi-objective problem of minimizing a vector of objective functions into a scalar problem by constructing a weighted sum of all the objectives. The problem can then be solved using a standard constrained optimization procedure. The proposed mixed integer linear model is solved by using the CPLEX solver. The solution obtained from the multi-objective problem allows us to identify days and products experiencing shortages. In such cases, when there is insufficient available inventory, the total quantity of product to be dispatched is redistributed among beneficiaries according to a pre-established prioritization. These redistributions are formulated as integer programming problems using a score-based criterion and solved by an exact method based on dynamic programming. Computational results demonstrate the applicability of the novel model for perishable items to a real-world study case.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"12 ","pages":"Article 100304"},"PeriodicalIF":2.5,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214716024000083/pdfft?md5=d4934e2ec81af99eee9488876b901256&pid=1-s2.0-S2214716024000083-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140948097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A recent review of solution approaches for green vehicle routing problem and its variants","authors":"Annisa Kesy Garside ,&nbsp;Robiah Ahmad ,&nbsp;Mohd Nabil Bin Muhtazaruddin","doi":"10.1016/j.orp.2024.100303","DOIUrl":"https://doi.org/10.1016/j.orp.2024.100303","url":null,"abstract":"<div><p>The green vehicle routing problem (GVRP) has been a prominent topic in the literature on logistics and transportation, leading to extensive research and previous review studies covering various aspects. Operations research has seen the development of various exact and approximation approaches for different extensions of the GVRP. This paper presents an up-to-date and thorough review of GVRP literature spanning from 2016 to 2023, encompassing 458 papers. significant contribution lies in the updated solution approaches and algorithms applied to both single-objective and multi-objective GVRP. Notably, 92.58 % of the papers introduced a mathematical model for GVRP, with many researchers adopting mixed integer linear programming as the preferred modeling approach. The findings indicate that both metaheuristics and hybrid are the most employed solution approaches for addressing single-objective GVRP. Among hybrid approaches, the combination of metaheuristics-metaheuristics is particularly favored by GVRP researchers. Furthermore, large neighborhood search (LNS) and its variants (especially adaptive large neighborhood search) emerges as the most widely adopted algorithm in single-objective GVRP. These algorithms are proposed within both metaheuristic and hybrid approaches, where A-/LNS is often combined with other algorithms. Conversely, metaheuristics are predominant in addressing multi-objective GVRP, with NSGA-II being the most frequently proposed algorithm. Researchers frequently utilize GAMS and CPLEX as optimization modeling software and solvers. Furthermore, MATLAB is a commonly employed programming language for implementing proposed algorithms.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"12 ","pages":"Article 100303"},"PeriodicalIF":2.5,"publicationDate":"2024-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214716024000071/pdfft?md5=c229fa600d5a6f4ce847c43d2270f761&pid=1-s2.0-S2214716024000071-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140823518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multiobjective approach for weekly Green Home Health Care routing and scheduling problem with care continuity and synchronized services","authors":"Salma Makboul ,&nbsp;Said Kharraja ,&nbsp;Abderrahman Abbassi ,&nbsp;Ahmed El Hilali Alaoui","doi":"10.1016/j.orp.2024.100302","DOIUrl":"https://doi.org/10.1016/j.orp.2024.100302","url":null,"abstract":"<div><p>Home Health Care (HHC) services are essential for delivering healthcare programs to patients in their homes, with the goal of reducing hospitalization rates and improving patients’ quality of life. However, HHC organizations face significant challenges in scheduling and routing caregivers for home care visits due to complex criteria and constraints. This paper addresses these challenges by considering both caregiver assignments and transportation logistics. The objective is to minimize the total travel distance and CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions while ensuring a balanced workload for caregivers, meeting patients’ preferences, synchronization, precedence, and availability constraints. To tackle this problem, we propose a multiperiodic Green Home Health Care (GHHC) framework. In the first stage, we utilize multiobjective programming and the NSGA-II algorithm to generate Pareto front solutions that consider travel distance and CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions. In the second stage, a Mixed-Integer Linear Programming (MILP) model is proposed to balance caregivers’ workload by assigning them to the patient routes generated in the first stage. The results highlight the trade-off between shorter routes and lower emissions. Furthermore, we examine the impact of prioritizing continuity of care and patient satisfaction. This research provides valuable insights into addressing the scheduling and routing challenges in HHC services, contributing to a more efficient and environmentally friendly healthcare delivery.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"12 ","pages":"Article 100302"},"PeriodicalIF":2.5,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S221471602400006X/pdfft?md5=505b0751c92c9b0e752439657d376e6b&pid=1-s2.0-S221471602400006X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140631675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards balancing efficiency and customer satisfaction in airplane boarding: An agent-based approach","authors":"Bruna H.P. Fabrin ,&nbsp;Denise B. Ferrari ,&nbsp;Eduardo M. Arraut ,&nbsp;Simone Neumann","doi":"10.1016/j.orp.2024.100301","DOIUrl":"https://doi.org/10.1016/j.orp.2024.100301","url":null,"abstract":"<div><p>The airplane boarding process, which can have a significant impact on a flight’s turnaround time, is often viewed by researchers and airlines primarily in terms of minimizing total boarding time (TBT). Airplane capacity, number of passengers on board, amount of luggage, and boarding strategy are common factors that affect TBT. However, besides operational efficiency, airlines are also concerned with customer satisfaction, which affects customer loyalty and financial return. One factor that influences passenger experience is the individual boarding time (IBT), here defined by the time passengers stand inside the cabin. Considering these two aspects, an agent-based model is presented that compares the performance of three alternative mainstream boarding strategies in a 132-seat and a 160-seat single-aisle commercial airplane. An important characteristic of the model that differentiates it from previous work is that overhead bins have a physical limitation, which could lead to an increase in aisle interferences on full flights as passengers take longer to find a place for their carry-on luggage. Another important contribution is the analysis of how passenger seat location affects IBT. Our results show that outside-in (OI) produces shorter TBT than random and back-to-front boarding, and also shorter IBT and much shorter maximum IBT than BTF, particularly for passengers seated in the middle of the airplane. This suggests that among the three most popular boarding strategies used by airlines across the world, OI is the best when it comes to balancing airplane boarding efficiency with individual customer satisfaction.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"12 ","pages":"Article 100301"},"PeriodicalIF":2.5,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214716024000058/pdfft?md5=ce629ea7008970f0da48b9d6d3c7291e&pid=1-s2.0-S2214716024000058-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140605264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Green retailer: A stochastic bi-level approach to support investment decisions in sustainable energy systems","authors":"Patrizia Beraldi","doi":"10.1016/j.orp.2024.100300","DOIUrl":"https://doi.org/10.1016/j.orp.2024.100300","url":null,"abstract":"<div><p>This paper presents a bi-level approach to support retailers in making investment decisions in renewable-based systems to provide clean electricity. The proposed model captures the strategic nature of the problem and combines capacity sizing decisions for installed technologies with pricing decisions regarding the electricity tariffs to offer to a reference end-user, representative of a class of residential prosumers. The interaction between retailer and end-user is modeled using the Stackelberg game framework, with the former acting as a leader and the latter as follower. The reaction of the follower to the electricity tariff affects the retailer’s profit, which is calculated as the difference between the revenue generated from selling electricity and the total investment, operation and management costs. To account for uncertainty in wholesale electricity prices, renewable resource availability and electricity request, the upper-level problem is formulated as a two-stage stochastic programming model. First-stage decisions refer to the sizing of installed technologies and electricity tariffs, whereas second-stage decisions refer to the operation and management of the designed system. The model also incorporates a safety measure to control the average profit that can be achieved in a given percentage of worst-case situations, thus providing a contingency against unforeseen changes. At the lower level, the follower reacts to the offered tariffs by defining the procurement plan in terms of energy to purchase from the retailer or potential competitors, with the final aim of minimizing the expected value of the electricity bill. A tailored approach that exploits the specific problem structure is designed to solve the proposed formulation and extensively tested on a realistic case study. The numerical results demonstrate the efficiency of the proposed approach and validate the significance of explicitly dealing with the uncertainty and the importance of incorporating a safety measure.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"12 ","pages":"Article 100300"},"PeriodicalIF":2.5,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214716024000046/pdfft?md5=10af9519673ad91c7f729f13bb913696&pid=1-s2.0-S2214716024000046-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}