
样式: 排序: IF: - GO 导出 标记为已读
-
Robust linear algebra Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-28 Dimitris Bertsimas, Thodoris Koukouvinos
We propose a robust optimization (RO) framework that immunizes some of the central linear algebra problems in the presence of data uncertainty. Namely, we formulate linear systems, matrix inversion, eigenvalues-eigenvectors and matrix factorization under uncertainty, as robust optimization problems using appropriate descriptions of uncertainty. The resulting optimization problems are computationally
-
Container port truck dispatching optimization using Real2Sim based deep reinforcement learning Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-28 Jiahuan Jin, Tianxiang Cui, Ruibin Bai, Rong Qu
In marine container terminals, truck dispatching optimization is often considered as the primary focus as it provides crucial synergy between the sea-side operations and yard-side activities and hence can greatly affect the terminal throughput and quay crane utilization. However, many existing studies rely on strong assumptions that often overlook the uncertainties and dynamics innate to real-life
-
Online reinforcement learning for condition-based group maintenance using factored Markov decision processes Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-28 Jianyu Xu, Bin Liu, Xiujie Zhao, Xiao-Lin Wang
We investigate a condition-based group maintenance problem for multi-component systems, where the degradation process of a specific component is affected only by its neighbouring ones, leading to a special type of stochastic dependence among components. We formulate the maintenance problem into a factored Markov decision process taking advantage of this dependence property, and develop a factored value
-
A note on “A unified solution framework for multi-attribute vehicle routing problems” Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-27 Thierry Garaix, Mohammed Skiredj
In this note, the authors propose correcting one erroneous formula from [Vidal, T., Crainic, T. G., Gendreau, M., & Prins, C. (2014). A unified solution framework for multi-attribute vehicle routing problems. European Journal of Operational Research, 234(3), 658-673] in charge of lunch breaks. In the original paper, the authors propose to compute several attribute values from the solution of a vehicle
-
Constructing copulas using corrected Hermite polynomial expansion for estimating cross foreign exchange volatility Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-25 Kenichiro Shiraya, Tomohisa Yamakami
A finite order multivariate Hermite polynomial expansion, as an approximation of a joint density function, can handle complex correlation structures. However, it does not construct copulas, because the density function can take negative values. In this study, we propose a formulation of multivariate Hermite polynomial expansion suitable for the application of correction that recovers non-negativity
-
Operations research approaches for improving coordination, cooperation, and collaboration in humanitarian relief chains: A framework and literature review Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-23 Birce Adsanver, Burcu Balcik, Valerie Bélanger, Marie-Ève Rancourt
Given the considerable number of actors in the humanitarian space, coordination is essential for successful disaster response. Furthermore, the sheer size of challenges and limited resources increasingly highlight the need for improved cooperation and collaboration in humanitarian supply chains. A significant number of studies in the literature explore the 3Cs (coordination, cooperation and collaboration)
-
Solidarity to achieve stability Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-24 Jorge Alcalde-Unzu, Oihane Gallo, Elena Inarra, Juan D. Moreno-Ternero
Agents may form coalitions. Each coalition shares its endowment among its agents by applying a sharing rule. The sharing rule induces a coalition formation problem by assuming that agents rank coalitions according to the allocation they obtain in the corresponding sharing problem. We characterize the sharing rules that induce a class of stable coalition formation problems as those that satisfy a natural
-
Designing electricity distribution networks: The impact of demand coincidence Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-24 Gunther Gust, Alexander Schlueter, Stefan Feuerriegel, Ignacio Ubeda, Jonathan T. Lee, Dirk Neumann
With the global effort to reduce carbon emissions, clean technologies such as electric vehicles and heat pumps are increasingly introduced into electricity distribution networks. These technologies considerably increase electricity flows and can lead to more coincident electricity demand. In this paper, we analyze how such increases in demand coincidence impact future distribution network investments
-
Sentiment Classification of Time-Sync Comments: A Semi-Supervised Hierarchical Deep Learning Method Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-23 Renzhi Gao, Xiaoyu Yao, Zhao Wang, Mohammad Zoynul Abedin
Time-sync comment (TSC) has emerged as a new type of textual comment for real-time user interactions on online video platforms. The sentiment classification of TSCs provides considerable potential for platforms to optimize operation strategies but inevitably faces great challenges due to the TSCs’ often uninformative and informal text. Considering the contextual dependency among TSCs posted within
-
Vehicle routing problems with multiple commodities: A survey Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-23 Wenjuan Gu, Claudia Archetti, Diego Cattaruzza, Maxime Ogier, Frédéric Semet, M. Grazia Speranza
In this paper, we present a survey on vehicle routing problems with multiple commodities. In most routing problems, only one commodity is explicitly considered. This may be due to the fact that, indeed, a single commodity is involved, or multiple commodities are transported, but they are aggregated and modeled as a single commodity, as no specific requirement imposes their explicit consideration. However
-
Risk pooling under demand and price uncertainty Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-22 Refik Güllü, Nesim Erkip
This paper studies purchasing a commodity or a perishable item under stochastically evolving and correlated prices for a distribution system environment. We consider the central purchasing of the commodity under the demand process correlated with the random price and decide on the timing and quantity of allocation to demand locations. As an implementation of the physical pooling concept, we investigate
-
Impacts of extreme weather events on mortgage risks and their evolution under climate change: A case study on Florida Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-19 Raffaella Calabrese, Timothy Dombrowski, Antoine Mandel, R. Kelley Pace, Luca Zanin
We develop an additive Cox proportional hazard model with time-varying covariates, including spatio-temporal characteristics of weather events, to study the impact of weather extremes (heavy rains and tropical cyclones) on the probability of mortgage default and prepayment. We compare the survival model with a flexible logistic model and an extreme gradient boosting algorithm. We estimate the models
-
A regularized interior point method for sparse optimal transport on graphs Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-19 S. Cipolla, J. Gondzio, F. Zanetti
In this work, the authors address the Optimal Transport (OT) problem on graphs using a proximal stabilized Interior Point Method (IPM). In particular, strongly leveraging on the induced primal–dual regularization, the authors propose to solve large scale OT problems on sparse graphs using a bespoke IPM algorithm able to suitably exploit primal–dual regularization in order to enforce scalability. Indeed
-
Exact and heuristic algorithms for minimizing the makespan on a single machine scheduling problem with sequence-dependent setup times and release dates Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-20 Rafael Morais, Teobaldo Bulhões, Anand Subramanian
This paper proposes efficient exact and heuristic approaches for minimizing the makespan on a single machine scheduling problem with sequence-dependent setup times and release dates. The exact procedure consists of a branch-and-price (B&P) algorithm implemented over an arc-time-indexed formulation with a pseudo-polynomial number of variables and constraints. Our B&P algorithm includes several modern
-
Blockchain adoption in retail operations: Stablecoins and traceability Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-19 Kun Zhang, Tsan-Ming Choi, Sai-Ho Chung, Yue Dai, Xin Wen
Retailers are embracing cryptocurrency payments to gain a competitive edge. However, the fierce volatility of traditional cryptocurrencies like Bitcoin deters risk-averse consumers from using them regularly. This issue is particularly pronounced in retail markets with high product return rates, as consumers may bear the volatility risk by directly holding cryptocurrencies after claiming a refund. In
-
Persistence in financial connectedness and systemic risk Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-17 Jozef Baruník, Michael Ellington
This paper characterises dynamic linkages arising from shocks with heterogeneous degrees of persistence. Using frequency domain techniques, we introduce measures that identify smoothly varying links of a transitory and persistent nature. Our approach allows us to test for statistical differences in such dynamic links. We document substantial differences in transitory and persistent linkages among US
-
Platform financing vs. bank financing: Strategic choice of financing mode under seller competition Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-18 Prasenjit Mandal, Preetam Basu, Tsan-Ming Choi, Sambit Brata Rath
Third-party sellers on online platforms primarily rely on banks to meet their financing requirements and are often constrained by the lack of sufficient working capital. Online platforms such as Amazon and Alibaba have ushered new dynamics in the e-commerce financing landscape by offering working capital loans to these sellers, thereby directly competing with banks and influencing market competition
-
Piecewise linear approximation with minimum number of linear segments and minimum error: A fast approach to tighten and warm start the hierarchical mixed integer formulation Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-18 Quentin Ploussard
In several areas of economics and engineering, it is often necessary to fit discrete data points or approximate non-linear functions with continuous functions. Piecewise linear (PWL) functions are a convenient way to achieve this. PWL functions can be modeled in mathematical problems using only linear and integer variables. Moreover, there is a computational benefit in using PWL functions that have
-
Setting the deadline and the penalty policy for a new environmental standard Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-17 Amirmohsen Golmohammadi, Tim Kraft, Seyedamin Monemian
A common approach that governments use to combat the potential environmental harm caused by industry is to set an environmental standard for firms to either comply with by a specified deadline or face a penalty. Two penalty policies that governments often rely on to pressure firms to comply with a new standard are a per-period penalty policy and a per-unit penalty policy. We examine how a government
-
Distributed mean reversion online portfolio strategy with stock network Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-17 Yannan Zhong, Weijun Xu, Hongyi Li, Weiwei Zhong
Online portfolio selection is a practical problem in financial engineering and quantitative trading. Many empirical studies show that stock performance in the market is likely to follow mean reversion, and strategies based on mean reversion show better return performance than the market average. However, the existing mean reversion strategies are not universal and short selling is not allowed, which
-
Single machine adversarial bilevel scheduling problems Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-17 Vincent T’kindt, Federico Della Croce, Alessandro Agnetis
We consider single machine scheduling problems in the context of adversarial bilevel optimization where two agents, the leader and the follower, take decisions on the same jobset and the leader acts first with the aim of inducing the worst possible solution for the follower. Thus, the follower schedules the jobs in order to optimize a given criterion. The considered criteria are the total completion
-
Column generation-based prototype learning for optimizing area under the receiver operating characteristic curve Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-16 Erhan C. Ozcan, Berk Görgülü, Mustafa G. Baydogan
The traditional classification algorithms focus on the maximization of classification accuracy which might lead to poor performance in practice by forcing classifiers to overfit to the majority class. In order to overcome this issue, various approaches focus on the optimization of alternative loss functions such as the Area Under the Curve (AUC). AUC is a Receiver Operating Characteristics (ROC) metric
-
A preference elicitation approach for the ordered weighted averaging criterion using solution choice observations Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-15 Werner Baak, Marc Goerigk, Michael Hartisch
Decisions under uncertainty or with multiple objectives usually require the decision maker to formulate a preference regarding risks or trade-offs. If this preference is known, the ordered weighted averaging (OWA) criterion can be applied to aggregate scenarios or objectives into a single function. Formulating this preference, however, can be challenging, as we need to make explicit what is usually
-
Supervised feature compression based on counterfactual analysis Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-15 Veronica Piccialli, Dolores Romero Morales, Cecilia Salvatore
Counterfactual Explanations are becoming a de-facto standard in post-hoc interpretable machine learning. For a given classifier and an instance classified in an undesired class, its counterfactual explanation corresponds to small perturbations of that instance that allows changing the classification outcome. This work aims to leverage Counterfactual Explanations to detect the important decision boundaries
-
Network design with route planning for battery electric high-speed passenger vessel services Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-14 Håkon Furnes Havre, Ulrik Lien, Mattias Myklebust Ness, Kjetil Fagerholt, Kenneth Løvold Rødseth
This paper studies the Zero Emission passenger Vessel Service Network Design Problem (ZEVSNDP) in order to investigate how technical and economic challenges related to diffusion of battery electric vessels can be alleviated by appropriate planning of services. The ZEVSNDP considers decisions that are strategic (i.e., vessel fleet and charging locations), tactical (i.e., routes, whether to omit servicing
-
What Makes Accidents Severe! Explainable Analytics Framework with Parameter Optimization Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-10 Abdulaziz Ahmed, Kazim Topuz, Murad Moqbel, Ismail Abdulrashid
Most analytics models are built on complex internal learning processes and calculations, which might be unintuitive, opaque, and incomprehensible to humans. Analytics-based decisions must be transparent and intuitive to foster greater human acceptability and confidence in analytics. Explainable analytics models are transparent models in which the primary factors and weights that lead to a prediction
-
A simulation-based approximate dynamic programming approach to dynamic and stochastic resource-constrained multi-project scheduling problem Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-10 U. Satic, P. Jacko, C. Kirkbride
We consider the dynamic and stochastic resource-constrained multi-project scheduling problem which allows for the random arrival of projects and stochastic task durations. Completing projects generates rewards, which are reduced by a tardiness cost in the case of late completion. Multiple types of resource are available, and projects consume different amounts of these resources when under processing
-
-
The impact of ambiguity on dynamic portfolio selection in the epsilon-contaminated binomial market model Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-09 Davide Petturiti, Barbara Vantaggi
We consider dynamic portfolio selection under ambiguity in the classical multi-period binomial market model. Ambiguity is incorporated in the real-world probability measure through an epsilon-contamination, that gives rise to a completely monotone capacity conveying a pessimistic investor’s ambiguous beliefs. The dynamic portfolio selection problem is formulated as a Choquet expected utility maximization
-
Approximation algorithms for scheduling parallel machines with an energy constraint in green manufacturing Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-08 Weidong Li, Jinwen Ou
Motivated by current green manufacturing standards, in this paper we study a parallel-machine scheduling model in which the energy cost incurred on each machine is machine-dependent and proportional to the load of the machine. The objective is to determine a production schedule with the minimum makespan subject to the energy constraint that the total energy cost does not exceed a given bound. We provide
-
The supply of convenience stores: Challenges of short-distance routing within the constraints of working time regulations Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-08 Manuel Ostermeier
Convenience stores are small shops typically located in dense urban areas. They are an important element in modern retailing considering growing urbanization. The layout of convenience stores usually differs significantly for individual stores depending on the local conditions and the types of store (e.g., grocery stores, kiosks, gas stations). Convenience stores have specific delivery requirements
-
An efficient and provable sequential quadratic programming method for American and swing option pricing Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-08 Jinye Shen, Weizhang Huang, Jingtang Ma
A sequential quadratic programming numerical method is proposed for American option pricing based on the variational inequality formulation. The variational inequality is discretized using the θ-method in time and the finite element method in space. The resulting system of algebraic inequalities at each time step is solved through a sequence of box-constrained quadratic programming problems, with the
-
A genetic algorithm with resource buffers for the resource-constrained multi-project scheduling problem Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-08 Dries Bredael, Mario Vanhoucke
In this study, we compose a new metaheuristic algorithm for solving the resource-constrained multi-project scheduling problem. Our approach is based on a general metaheuristic strategy which incorporates two resource-buffered scheduling tactics. We build on the most effective evolutionary operators and other well-known scheduling methods to create a novel genetic algorithm with resource buffers. We
-
Optimal control policies for dynamic inventory systems with service level dependent demand Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-07 Xiaoming Yan, Xiuli Chao, Ye Lu
Empirical studies have shown that stockouts may adversely affect future demand. However, much of the literature on inventory optimization has ignored this effect. In this paper, we investigate the effect of stockouts on a firm’s operational policy and total discounted profit. We show that compared with classic periodic review inventory models with no stockout effect, the optimal inventory control policies
-
Should original equipment manufacturers authorize third-party remanufacturers? Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-07 Wei Li, Mingzhou Jin, Michael R. Galbreth
Remanufacturing is well-established as a means for original equipment manufacturers (OEMs) to reduce waste, save on raw materials costs, and tap into new markets. At the same time, OEMs are often skeptical of remanufacturing due to the potential for remanufactured items to steal market share from new items. Third-party remanufacturers (TPRs) experience no such skepticism, since these market players
-
Multicommodity international agricultural trade network equilibrium: Competition for limited production and transportation capacity under disaster scenarios with implications for food security Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-07 Anna Nagurney, Dana Hassani, Oleg Nivievskyi, Pavlo Martyshev
The number of people affected by disasters, including man-made ones, is on the rise globally, with rising food insecurity being one of the most critical impacts. Disasters, both sudden-onset and slow-onset ones, can cause disruptions to the production and transportation of agricultural commodities. Having the tools that can quantitatively assess the changes in agricultural commodity shipment volumes
-
Freight railcar-to-train assignment and departure scheduling in a railyard Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-07 Mina Aliakbari, Joseph Geunes, Amir Ghahari, Mike Prince
Rail freight distribution operations require assembling trains consisting of multiple freight cars with a common destination, and assigning departure times to the assembled trains. Limits on railyard train assembly capacity restrict the number of trains that may be assembled and, therefore, depart the railyard, per unit time. Each individual car, or unit, in a railyard typically has an associated subsequent
-
Operational Research for, with, and by citizens: an overview Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-04 Alice H. Aubert, Judit Lienert
Interest in citizen participation is increasing generally. Almost all operational research (OR) is engaged with clients, but it is mainly in the areas of Soft and Community OR that wider stakeholder and citizen participation has been a significant focus. It is the involvement of citizens that is the subject of this paper. We surveyed OR literature and compiled a corpus of 62 studies, the earliest from
-
Machine scheduling with restricted rejection: An Application to task offloading in cloud–edge collaborative computing Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-04 Weidong Li, Jinwen Ou
With the burgeoning of the Internet of everything, the amount of data generated by edge devices increases dramatically. In order to relieve the huge pressure of the could computing center, a popular computing scheme, called edge computing, is to select and process part of the computation tasks on edge servers of the network. In this paper we model the task offloading problem motivated by the popular
-
The impact of blockchain on restricting the misuse of green loans in a capital-constrained supply chain Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-04 Minxue Wang, Bo Li, Dongping Song
Nowadays, green loans have been widely promoted to support the capital-constrained supply chain under carbon regulation. However, the borrowers in the supply chain may use the preferential green loans for other purposes which are not related to green development. That phenomenon is mainly attributed to the lack of valid information investigation under traditional information technology. Blockchain
-
Less is more? Channel separation to mitigate triple competition and combat copycats in agency e-commerce Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-03 Baozhuang Niu, Yiyuan Ruan, Haotao Xu
In practice, agency e-commerce, also known as e-marketplace, faces the challenges of copycat products with nearly identical “consumption quality” to genuine products. The e-marketplace may lack incentives to combat copycat sellers, leading many brands to adopt a novel “Channel Separation” strategy to protect their brand image. Under this strategy, although the brand seems to lose profit from stopping
-
On the paper “Augmented Lagrangian algorithms for solving the continuous nonlinear resource allocation problem” Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-02 L.F. Bueno, G. Haeser, O. Kolossoski
In the paper Torrealba et al. (2021) an augmented Lagrangian algorithm was proposed for resource allocation problems with the intriguing characteristic that instead of solving the box-constrained augmented Lagrangian subproblem, they propose projecting the solution of the unconstrained subproblem onto such box. A global convergence result for the quadratic case was provided, however, this is somewhat
-
Minimax regret stability in the graph model for conflict resolution Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-02 Emerson Rodrigues Sabino, Leandro Chaves Rêgo
In strategic conflicts, decision-makers (DMs) do not constantly make their best decisions, which makes room for DMs to feel regretful. In this context, this work proposes the Minimax Regret Stability within the graph model for conflict resolution (GMCR) for modelling and analysing conflicts, considering that DMs would feel regret for an unsatisfactory decision. This concept does not require knowledge
-
Simulation schemes for the Heston model with Poisson conditioning Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-02 Jaehyuk Choi, Yue Kuen Kwok
Exact simulation schemes under the Heston stochastic volatility model (e.g., Broadie–Kaya and Glasserman–Kim) suffer from computationally expensive Bessel function evaluations. We propose a new exact simulation scheme without the Bessel function, based on the observation that the conditional integrated variance can be simplified when conditioned by the Poisson variate used for simulating the terminal
-
Hierarchy selection. New team ranking indicators for cyclist multi-stage races Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-02 Marcel Ausloos
In this paper, I report some investigation discussing team selection, whence hierarchy, through ranking indicators, for example when “measuring” professional cyclist team’s “sportive value”, in particular in multistage races. A logical, it seems, constraint is introduced on the riders: they must finish the race. Several new indicators are defined, justified, and compared. These indicators are mainly
-
A copula-based approach to modelling the failure process of items under two-dimensional warranty and applications Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-02 Shaomin Wu
Hundreds of scholarly papers on optimisation of preventive maintenance policies for items under warranty have been published in the reliability related literature. They typically have two limitations: they make a simplified assumption on the relationship between age and usage for items under two-dimensional warranty and they assume that it is cost-effective to conduct preventive maintenance (PM) on
-
A lexicographically optimal completion for pairwise comparison matrices with missing entries Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-02 Kolos Csaba Ágoston, László Csató
Estimating missing judgements is a key component in many multi-criteria decision making techniques, especially in the Analytic Hierarchy Process. Inspired by the Koczkodaj inconsistency index and a widely used solution concept of cooperative game theory called the nucleolus, the current study proposes a new algorithm for this purpose. In particular, the missing values are substituted by variables,
-
The family capacitated vehicle routing problem Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-01 Raquel Bernardino, Ana Paias
In this article, we address the family capacitated vehicle routing problem (F-CVRP), an NP-hard problem that generalizes both the FTSP and the capacitated vehicle routing problem. The F-CVRP has practical application in warehouse management in warehouses with scattered storage. We present several mixed integer linear programming formulations for this problem and establish a theoretical and empirical
-
An expandable machine learning-optimization framework to sequential decision-making Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-11-01 Dogacan Yilmaz, İ. Esra Büyüktahtakın
We present an integrated prediction-optimization (PredOpt) framework to efficiently solve sequential decision-making problems by predicting the values of binary decision variables in an optimal solution. We address the key issues of sequential dependence, infeasibility, and generalization in machine learning (ML) to make predictions for optimal solutions to combinatorial problems. The sequential nature
-
When is the next order? Nowcasting channel inventories with Point-of-Sales data to predict the timing of retail orders Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-10-31 Tim Schlaich, Kai Hoberg
Slow-moving goods are common in many retail settings and occupy a vast part of retail shelves. Since stores sell these products irregularly and in small quantities, the replenishing distribution center may only place batched orders with manufacturers every few weeks. While order quantities are often fixed, the challenge for manufacturers facing such intermittent demand is to forecast the order timing
-
The bright side of the planning fallacy in distribution channels Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-10-31 Michael Kopel, Vinay Ramani
The planning fallacy describes the tendency of people to underestimate the costs and to overestimate the benefits of investments. It is typically associated with cost overruns and decreased performance. In this paper, we demonstrate that in a simple distribution channel with an upstream manufacturer and a downstream retailer that both make demand-enhancing investments, there is a bright side of the
-
Competitive location models: A review Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-10-31 Zvi Drezner, H.A. Eiselt
The objective of facility location models is to maximize the profit or minimize the cost of a company that wishes to expand or enter the market. The market share captured by facilities is a function of the distances to the facilities and their attractiveness. The analysis involves how to estimate the market share captured by facilities, where to locate new facilities, how to determine their attractiveness
-
Simplifying tree-based methods for retail sales forecasting with explanatory variables Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-10-31 Arnoud P. Wellens, Robert N. Boute, Maximiliano Udenio
Despite being consistently outperformed by machine learning (ML) in forecasting competitions, simple statistical forecasting techniques remain standard in retail. This is partly because, for all their advantages, these top-performing ML methods are often too complex to implement. We have experimented with various tree-based ML methods and find that a ‘simple’ implementation of these can (substantially)
-
Government Subsidy Policies for Guarantee Financing: Risk Compensation vs. Fee Reduction Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-10-29 Luping Luo, Wen He, Hao Hu
Small and medium-sized enterprises (SMEs) often rely on credit guarantee companies (guarantors) to obtain financing from banks. To encourage guarantors’ engagement and reduce SMEs’ guarantee costs, governments commonly implement two subsidy policies: risk compensation, which shares a fraction of guarantors’ losses, and fee reduction, which reimburses SMEs for a fraction of their guarantee fees. This
-
Facility location decisions for drone delivery: A literature review Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-10-30 Okan Dukkanci, James F. Campbell, Bahar Y. Kara
This study presents a comprehensive literature survey on facility location problems for drone (uncrewed vehicle) delivery, where either (i) drones are the only vehicles, or (ii) drones and other vehicles (e.g., trucks) work together for delivery, but drones do not ride in or on the other vehicles. The main goals of this review are to identify and categorize fundamental facility location problems associated
-
Power structure preferences in a dual-channel supply chain: Demand information symmetry vs. asymmetry Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-10-30 Xiaoqing Hu, Jianhu Cai, Xiaohang Yue
This study establishes a dual-channel supply chain (DCSC) wherein the e-retailer is endowed with superior demand information, and investigates power structure preferences of the supplier and e-retailer. Game models are investigated based on two information structures (information symmetry and asymmetry) and three power structures, i.e., vertical Nash, e-retailer-led Stackelberg, and supplier-led Stackelberg
-
A new cross-efficiency meta-frontier analysis method with good ability to identify technology gaps Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-10-30 Ruiyue Lin, Yudan Peng
Cross-efficiency evaluation and meta-frontier analysis (MFA) have been widely used to measure performance in many areas. However, cross-efficiency MFA (CMFA) has rarely been studied due to its potential violation of the basic MFA property, that is, the efficiency relative to the group frontier is not less than that relative to the meta-frontier. In this paper, we deduce the conditions under which the
-
Can online interfaces enhance learning for public decision-making? Eliciting citizens’ preferences for multicriteria decision analysis Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-10-29 Alice H. Aubert, Sara Schmid, Judit Lienert
Innovative online interfaces informing and consulting citizens about their preferences for multicriteria decision analysis (MCDA) could make public decision-making more participatory. We propose a three-faceted learning for decision-making framework and used it to test newly-designed online weight elicitation interfaces. We investigated two features meant to enhance learning: fully-fledged gamification
-
Cluster ensemble selection and consensus clustering: A multi-objective optimization approach Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-10-29 Dilay Aktaş, Banu Lokman, Tülin İnkaya, Gilles Dejaegere
Cluster ensembles have emerged as a powerful tool to obtain clusters of data points by combining a library of clustering solutions into a consensus solution. In this paper, we address the cluster ensemble selection problem and design a multi-objective optimization-based solution framework to produce consensus solutions. Given a library of clustering solutions, we first design a preprocessing procedure
-
A target-time-windows technique for project scheduling under uncertainty Eur. J. Oper. Res. (IF 6.4) Pub Date : 2023-10-26 Patricio Lamas, Marcos Goycoolea, Bernardo Pagnoncelli, Alexandra Newman
We address the problem of determining the start times of activities in order to maximize the expected net present value of a project given precedence constraints. We assume that each activity has a random duration and profit with a known probability distribution. Most approaches generate either: a baseline schedule that is robust to uncertainty (using proactive approaches), or a policy that reacts