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Mathematical optimisation in the honeycomb cardboard industry: A model for the two-dimensional variable-sized cutting stock problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-22 Paula Terán-Viadero, Antonio Alonso-Ayuso, F. Javier Martín-Campo
This paper presents a mixed-integer linear programming model for a two-dimensional variable-sized cutting stock problem with guillotine cuts that arises in the honeycomb cardboard sector. This research is developed in collaboration with a company based in Spain. The aim is not only to define the cutting patterns but also to establish the dimensions (width and length) of the panels to be produced, in
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A bilevel programming approach to price decoupling in Pay-as-Clear markets, with application to day-ahead electricity markets Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-22 Antonio Frangioni, Fabrizio Lacalandra
Motivated by the recent crisis of the European electricity markets, we propose the concept of (SPaC) market, introducing a new family of market clearing problems that achieve a degree of decoupling between groups of participants. This requires a relatively straightforward modification of the standard PaC model and retains its crucial features by providing both long- and short-term sound price signals
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Nonparametric multi-product dynamic pricing with demand learning via simultaneous price perturbation Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-21 Xiangyu Yang, Jianghua Zhang, Jian-Qiang Hu, Jiaqiao Hu
We consider the problem of multi-product dynamic pricing with demand learning and propose a nonparametric online learning algorithm based on the simultaneous perturbation stochastic approximation (SPSA) method. The algorithm uses only two price experimentations at each iteration, regardless of problem dimension, and could be especially efficient for solving high-dimensional problems. Under moderate
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Solving constrained consumption–investment problems by decomposition algorithms Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-20 Bernardo K. Pagnoncelli, Tito Homem-de-Mello, Guido Lagos, Pablo Castañeda, Javier García
Consumption–investment problems with maximizing utility agents are usually considered from a theoretical viewpoint, aiming at closed-form solutions for the optimal policy. However, such an approach requires that the model be relatively simple: even the inclusion of nonnegativity constraints can prevent the derivation of explicit solutions. In such cases, it is necessary to solve the problem numerically
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An exact algorithm for the multi-trip vehicle routing problem with time windows and multi-skilled manpower Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-20 Nan Huang, Hu Qin, Yuquan Du, Li Wang
Motivated by the challenges of non-emergency patient transportation services in the healthcare industry, this study investigated a multi-trip vehicle routing problem incorporating multi-skilled manpower with downgrading. We aimed to find an optimal plan for vehicle routing and multi-skilled manpower scheduling in tandem with the objective of minimizing the total cost, including travel and staff costs
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Investment–consumption optimization with transaction cost and learning about return predictability Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-17 Ning Wang, Tak Kuen Siu
In this paper, we investigate an investment–consumption optimization problem in continuous-time settings, where the expected rate of return from a risky asset is predictable with an observable factor and an unobservable factor. Based on observable information, a decision-maker learns about the unobservable factor while making investment–consumption decisions. Both factors are supposed to follow a mean-reverting
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Real-time train timetabling with virtual coupling operations on a Y-type metro line Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-15 Hongyang Wang, Lixing Yang, Jinlei Zhang, Qin Luo, Zhongsheng Fan
The spatiotemporal imbalance of passenger flows is a prominent characteristic of urban rail transit systems. To match the provided transportation capacity with passenger distribution, this study considers an integer linear programming model to optimize train operation on a Y-type line, including the train timetable, rolling stock circulation plan and virtual coupling/uncoupling strategy that enables
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Sequentially extending space-filling experimental designs by optimally permuting and stacking columns of the design matrix Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-15 J.D. Parker Jr., T.W. Lucas, W.M. Carlyle
Researchers make available computationally expensive designs for computer experiments for widespread use by cataloging them and providing online links. This paper presents an algorithm that augments space-filling designs (SFDs) by optimally permuting and stacking columns of the design matrix to minimize the maximum absolute pairwise correlation among columns in the new extended design. The algorithm
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Adaptive stochastic lookahead policies for dynamic multi-period purchasing and inventory routing Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-15 Daniel Cuellar-Usaquén, Marlin W. Ulmer, Camilo Gomez, David Álvarez-Martínez
We explore a problem faced by agri-food e-commerce platforms in purchasing different, perishable products and collecting them from multiple producers and delivering them to a single warehouse, aiming to maintain adequate inventory levels to meet current and future customer demand, while avoiding waste. Customer demand and suppliers’ purchase prices and supply volumes are uncertain and revealed on a
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Russell and slack-based measures of efficiency: A unifying framework Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-12 Valentin Zelenyuk, Shirong Zhao
Some of the popular technical efficiency measures are not able to account for potential slacks in inputs or outputs and may misrepresent the degree of inefficiency pertinent to firms, industries, and countries when compared to their peers. A wide range of methods have been proposed in the literature over the last four decades to address this important issue. The precise relationship among many of these
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A review of recent advances in time-dependent vehicle routing Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-11 Tommaso Adamo, Michel Gendreau, Gianpaolo Ghiani, Emanuela Guerriero
In late 2015 three of the co-authors of this paper published the first review on time-dependent routing problems. Since then, there have been several important algorithmic developments in the field. These include travel time prediction methods, real-time re-optimization by operating directly on the road graph, efficient exploration of solution neighborhoods, dynamic discretization discovery and -inspired
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An effective multi-level memetic search with neighborhood reduction for the clustered team orienteering problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-11 Mu He, Qinghua Wu, Una Benlic, Yongliang Lu, Yuning Chen
The Clustered Team Orienteering Problem (CluTOP) extends the classic Clustered Orienteering Problem by considering the use of multiple vehicles. The problem is known to be NP-hard and can be used to formulate many real-life applications. This work presents a highly effective multi-level memetic search for CluTOP that combines a backbone-based edge assembly crossover to generate promising offspring
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A learning-based granular variable neighborhood search for a multi-period election logistics problem with time-dependent profits Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-11 Masoud Shahmanzari, Renata Mansini
Planning the election campaign for leaders of a political party is a complex problem. The party representatives, running mates, and campaign managers have to design an efficient routing and scheduling plan to visit multiple locations while respecting time and budget constraints. Given the limited time of election campaigns in most countries, every minute should be used effectively, and there is very
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Performance evaluation using multi-stage production frameworks: Assessing the tradeoffs among the economic, environmental, and social well-being Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-11 Yiran Niu, Jean-Philippe Boussemart, Zhiyang Shen, Michael Vardanyan
Aiming to achieve sustainable development, a constantly growing number of countries have strived to promote economic growth while simultaneously mitigating environmental degradation and maximizing social welfare. However, despite the importance attributed to social well-being in contemporary discourse, its role has not received much attention in the performance evaluation literature. We propose a novel
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A machine learning approach to two-stage adaptive robust optimization Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-10 Dimitris Bertsimas, Cheol Woo Kim
We propose an approach based on machine learning to solve two-stage linear adaptive robust optimization (ARO) problems with binary here-and-now variables and polyhedral uncertainty sets. We encode the optimal here-and-now decisions, the worst-case scenarios associated with the optimal here-and-now decisions, and the optimal wait-and-see decisions into what we denote as the strategy. We solve multiple
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Using anticipatory orders to manage disruption risk over a short product life cycle Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-10 Sunil Chopra, Vadim Glinskiy, Florian Lücker
We study the impact of supply disruptions on sourcing strategies when product life cycles are short and future demand depends on current sales. We introduce the concept of order policies with anticipatory orders where some or all of orders with the unreliable supplier in future periods are moved to an earlier period. Using a 2-period model, we show that despite incurring additional holding cost when
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Some new clique inequalities in four-index hub location models Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-10 Mercedes Landete, Juanjo Peiró
Hub location problems can be modeled in several ways, one of which is the path-based family of models that make use of four-index variables. Clique inequalities are frequently used to describe solution characteristics for optimization problems with binary variables. In this study, new valid inequalities of the clique type are introduced for the path-based family of hub location models. Some of their
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Agency or reselling? Supplier’s online channel strategies with platform financing Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-08 Yang Liu, Jizhou Lu, Nina Yan
Online finance implemented by e-commerce platforms assists small and medium-sized enterprises in overcoming capital shortages and advancing channel development. We investigate the interplay between channel strategy and platform financing within a dual-channel supply chain comprising a capital-constrained supplier, an e-commerce platform, and an offline retailer. The supplier has access to various sales
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Multicriteria optimization techniques for understanding the case mix landscape of a hospital Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-07 Robert L Burdett, Paul Corry, Prasad Yarlagadda, David Cook, Sean Birgan
Various medical and surgical units operate in a typical hospital and to treat their patients these units compete for infrastructure like operating rooms (OR) and ward beds. How that competition is regulated affects the capacity and output of a hospital. This article considers the impact of treating different patient case mix (PCM). As each case mix has an economic consequence and a unique profile of
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The generator distribution problem for base stations during emergency power outage: A branch-and-price-and-cut approach Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-06 Hu Qin, Anton Moriakin, Gangyan Xu, Jiliu Li
Motivated by the need for uninterrupted service provision in the telecommunications industry, this paper presents a novel problem concerning the transportation of diesel generators during an unplanned power outage. Given a set of base stations, each equipped with a capacitated back-up battery pack, the problem consists in finding an optimal delivery and pick-up schedule that minimises corresponding
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Which algorithm to select in sports timetabling? Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-06 David Van Bulck, Dries Goossens, Jan-Patrick Clarner, Angelos Dimitsas, George H.G. Fonseca, Carlos Lamas-Fernandez, Martin Mariusz Lester, Jaap Pedersen, Antony E. Phillips, Roberto Maria Rosati
Any sports competition needs a timetable, specifying when and where teams meet each other. The recent International Timetabling Competition (ITC2021) on sports timetabling showed that, although it is possible to develop general algorithms, the performance of each algorithm varies considerably over the problem instances. This paper provides a problem type analysis for sports timetabling, resulting in
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On the automatic generation of metaheuristic algorithms for combinatorial optimization problems Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-06 Raúl Martín-Santamaría, Manuel López-Ibáñez, Thomas Stützle, J. Manuel Colmenar
Metaheuristic algorithms have become one of the preferred approaches for solving optimization problems. Finding the best metaheuristic for a given problem is often difficult due to the large number of available approaches and possible algorithmic designs. Moreover, high-performing metaheuristics often combine general-purpose and problem-specific algorithmic components. We propose here an approach for
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An improved equilibrium efficient frontier data envelopment analysis approach for evaluating decision-making units with fixed-sum outputs Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-05 Junfei Chu, Yanhua Dong, Zhe Yuan
In recent years, significant development has been made in efficiency evaluation for Decision-Making Units (DMUs) with fixed-sum outputs. The Generalized Equilibrium Efficient Frontier Data Envelopment Analysis (GEEFDEA) approach introduced by Yang et al. (2015) is one of the most representative methods. In the GEEFDEA approach, all DMUs are adjusted to become efficient under the same set of weights
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A theory of multivariate stress testing Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-05 Pietro Millossovich, Andreas Tsanakas, Ruodu Wang
We present a theoretical framework for stressing multivariate stochastic models. We consider a stress to be a change of measure, placing a higher weight on multivariate scenarios of interest. In particular, a is a mapping from random vectors to Radon–Nikodym densities. We postulate desirable properties for stressing mechanisms addressing alternative objectives. Consistently with our focus on dependence
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Scalable policies for the dynamic traveling multi-maintainer problem with alerts Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-04 Peter Verleijsdonk, Willem van Jaarsveld, Stella Kapodistria
Downtime of industrial assets such as wind turbines and medical imaging devices is costly. To avoid such downtime costs, companies seek to initiate maintenance just before failure, which is challenging because: (i) Asset failures are notoriously difficult to predict, even in the presence of real-time monitoring devices which signal degradation; and (ii) Limited resources are available to serve a network
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Efficient use of collision detection for volume maximization problems Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-06-01 Jonas Tollenaere, Hatice Çalık, Tony Wauters
This paper proposes improved local search heuristics based on collision detection for solving volume maximization problems, with a particular focus on single item volume maximization. The objective is to find the biggest item of a predefined shape that can be extracted from a larger container. Both the item and the container are three-dimensional objects and can have irregular shapes. Our goal is to
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Double hedonic price-characteristics frontier estimation for IoT service providers in the industry 5.0 era: A nonconvex perspective accommodating ratios Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-29 Kristiaan Kerstens, Majid Azadi, Reza Kazemi Matin, Reza Farzipoor Saen
The advent of advanced digital technologies, including the Internet of Things (IoT), image processing, artificial intelligence (AI), blockchain, robotics and cognitive computing that have been embedded in Industry 5.0, is considerably improving the sustainability, resilience, and human-centric performance of industrial organizations. Despite the increasing use of Industry 5.0 technologies in smart
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Data-driven resource allocation for multi-target attainment Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-29 Dohyun Ahn
We delve into a class of multi-target attainment problems, which commonly arise in practical applications such as operations management, marketing, policy making, and healthcare services. The aim is to efficiently allocate a fixed amount of resources to achieve predetermined target payoffs for multiple tasks. We transform this stochastic problem into a tractable optimization problem that, when optimized
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Unexpected opportunities in misspecified predictive regressions Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-29 Guillaume Coqueret, Romain Deguest
This article documents surprising learning patterns that can occur under model misspecification. An agent resorts to predictive regressions and fails to take into account autocorrelation in the dependent variable. Remarkably, when the dependent and independent variables are uncorrelated, we find cases for which the resulting out-of-sample is well above zero, which benefits the agent, in spite of the
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Benders Decomposition with Delayed Disaggregation for the Active Passive Vehicle Routing Problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-29 Yannik Rist, Christian Tilk, Michael Forbes
We investigate a new exact solution approach for the Active Passive Vehicle Routing Problem, a vehicle routing problem with complicated temporal synchronisation requirements between vehicles. A key contribution is the introduction of a new principle, , for Benders Decomposition to produce disaggregated optimality cuts when traditional block-diagonality fails. The technique is applied to a new Mixed
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The digital economy and advertising diffusion models: Critical mass and the Stalling equilibrium Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-28 Gustav Feichtinger, Dieter Grass, Richard F. Hartl, Peter M. Kort, Andrea Seidl
In the digital economy it is frequently observed that products become more valuable the larger is the number of people that use it. To account for such network effects, we introduce a new diffusion equation in a dynamic model of the firm with the aim to obtain the advertising policy that maximizes firm profits. Also an advertising budget is introduced.
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Non-additive network pricing with non-cooperative mobility service providers Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-28 Wentao Huang, Sisi Jian, David Rey
This study addresses a mobility network pricing problem in a competitive environment. We consider a multimodal transportation network where the links are operated by multiple profit-maximizing, mobility service providers (MSPs). We take the perspective of a network regulator that aims to increase ridership in a target mobility network by providing non-additive, path-based subsidies to travelers. We
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A preventive maintenance policy and a method to approximate the failure process for multi-component systems Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-28 Shaomin Wu, Majid Asadi
Numerous maintenance policies have been proposed in the reliability mathematics and engineering literature. Nevertheless, little has been reported on their practical applications in industries. This gap is largely due to restrictive assumptions of the maintenance policies. Two of the main assumptions are that maintenance is conducted on typical components and that the reliability of an item under maintenance
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A queueing-based approach for integrated routing and appointment scheduling Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-28 René Bekker, Bharti Bharti, Leon Lan, Michel Mandjes
This paper aims to address the integrated routing and appointment scheduling (RAS) problem for a single service provider. The RAS problem is an operational challenge faced by operators that provide services requiring home attendance, such as grocery delivery, home healthcare, or maintenance services. While considering the inherently random nature of service and travel times, the goal is to minimize
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A hybrid genetic algorithm with type-aware chromosomes for Traveling Salesman Problems with Drone Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-24 Sasan Mahmoudinazlou, Changhyun Kwon
There are emerging transportation problems known as the Traveling Salesman Problem with Drone (TSPD) and the Flying Sidekick Traveling Salesman Problem (FSTSP) that involve using a drone in conjunction with a truck for package delivery. This study presents a hybrid genetic algorithm for solving TSPD and FSTSP by incorporating local search and dynamic programming. Similar algorithms exist in the literature
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Accelerated evaluation of blocking flowshop scheduling with total flow time criteria using a generalized critical machine-based approach Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-23 Yuyan Han, Yuting Wang, Quan-ke Pan, Ling Wang, M. Fatih Tasgetiren
Despite the considerable advances in the research of the blocking flowshop scheduling problem (BFSP), several unresolved challenges persist. Algorithmic complexity presents hurdles. Although the insertion-based method is considered to generate superior solutions, its high computational demand diminishes the efficiency of algorithms, especially within large-scale sequences. The existing accelerated
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A risk-averse distributionally robust project scheduling model to address payment delays Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-21 Maria Elena Bruni, Öncü Hazır
Delays in payments have become a common risk factor for industrial projects, especially in recent years, since the financial position of firms has been threatened by pandemics, wars, inflation, and major supply chain disruptions. These delays create a time lag between expenses and payments, potentially leading to cash shortages that can have significant negative effects on the project success. To address
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Competition or cooperation: Strategy analysis for a social commerce platform Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-21 Haiqing Song, Rui Wang, Yanli Tang
Consider a market where identical products are sold to consumers via two competing platforms: one traditional and the other social-commerce-based. The social commerce platform operates a virtual community using two strategies: a competition strategy whereby the social commerce platform attracts and engages consumers through its virtual community, leading them to directly purchase products from its
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Automated feeder routing for underground electricity distribution networks based on aerial images Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-20 Justus Ameling, Gunther Gust
The process towards a carbon-neutral society requires a substantial amount of investment into electricity distribution networks for integrating more sustainable technologies such as photovoltaic systems, electric vehicles, heat pumps, and others. In order to execute the large number of network expansion measures associated with this effort, strategic and operational planning of distribution networks
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Ensuring neonatal human milk provision: A framework for estimating potential demand for donor human milk Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-19 Marta Staff, Navonil Mustafee, Natalie Shenker, Gillian Weaver
Using donor human milk (DHM) for preterm infants, where the mother's milk is unavailable, protects infants against potentially fatal necrotising enterocolitis. When used optimally, DHM can support mothers to establish breastfeeding. Understanding the relationship between clinical choices for DHM provision and the resulting demand is important. For policymakers, it informs decision-making around the
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A competitive heuristic algorithm for vehicle routing problems with drones Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-19 Xuan Ren, Aurélien Froger, Ola Jabali, Gongqian Liang
We propose a heuristic algorithm capable of handling multiple variants of the vehicle routing problem with drones (VRPD). Assuming that the drone may be launched from a node and recovered at another, these variants are characterized by three axes, (1) minimizing the transportation cost or minimizing the makespan, (2) the drone is either allowed or not allowed to land while awaiting recovery, and (3)
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The rail-road Dial-a-Ride problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-18 Jean Jodeau, Nabil Absi, Rémy Chevrier, Dominique Feillet
This paper addresses an original static Dial-A-Ride service designed for sparsely populated areas. The service relies on vehicles capable of switching between the road and an existing vacant railway network, which induces railway scheduling constraints that must be integrated into the solution algorithm. In the context of the static Dial-A-Ride Problem (DARP), a set of known users must be picked up
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Worst-case Conditional Value at Risk for asset liability management: A framework for general loss functions Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-18 Alireza Ghahtarani, Ahmed Saif, Alireza Ghasemi
Asset–liability management (ALM) is a challenging task faced by pension funds due to the uncertain nature of future asset returns, employees’ wages, and interest rates. To address this challenge, this paper presents a new mathematical model that uses a Worst-case Conditional Value-at-Risk (WCVaR) constraint to ensure that, with high probability, the funding ratio remains above a regulator-mandated
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A review and ranking of operators in adaptive large neighborhood search for vehicle routing problems Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-18 Stefan Voigt
This article systematically reviews the literature on adaptive large neighborhood search (ALNS) to gain insights into the operators used for vehicle routing problems (VRPs) and their effectiveness. The ALNS has been successfully applied to a variety of optimization problems, particularly variants of the VRP. The ALNS gradually improves an initial solution by modifying it using removal and insertion
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On solving close enough orienteering problems with overlapped neighborhoods Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-17 Qiuchen Qian, Yanran Wang, David Boyle
The Close Enough Traveling Salesman Problem (CETSP) is a well-known variant of the classic Traveling Salesman Problem whereby the agent may complete its mission at any point within a target neighborhood. Heuristics based on overlapped neighborhoods, known as Steiner Zones (SZ), have gained attention in addressing CETSPs. While SZs offer effective approximations to the original graph, their inherent
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Scheduling with jobs at fixed positions Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-17 Florian Jaehn
In this paper, we study classical single machine scheduling problems with the additional constraint that a set of special jobs must be scheduled at certain positions in the job sequence. In other words, a special job must start when a certain number of jobs have finished on the machine. We analyze several classical objective functions for this more general setting with the additional constraint of
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Should live broadcasting platforms adopt artificial intelligence? A sales effort perspective Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-16 Xiaoping Xu, Yuting Wang, T.C.E. Cheng, Tsan-Ming Choi
We analytically investigate a supply chain (SC) that is composed of a manufacturer and a live broadcasting platform, and examine whether the latter should adopt artificial intelligence (AI) considering sales effort. We consider several important factors that affect the SC partners’ decision-making including live broadcasting power, consumer expectations of the product, and unfit probability that the
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Dynamic resource matching in manufacturing using deep reinforcement learning Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-15 Saunak Kumar Panda, Yisha Xiang, Ruiqi Liu
Matching plays an important role in the logical allocation of resources across a wide range of industries. The benefits of matching have been increasingly recognized in manufacturing industries. In particular, capacity sharing has received much attention recently. In this paper, we consider the problem of dynamically matching demand-capacity types of manufacturing resources. We formulate the multi-period
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Drone resupply with multiple trucks and drones for on-time delivery along given truck routes Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-15 Wenqian Liu, Lindong Liu, Xiangtong Qi
Drones have been increasingly used for deliveries; however, delivering packages directly to customers is still challenging, particularly in densely populated urban areas. To overcome this, drone resupply has been proposed, where drones carry packages to trucks en route, and then trucks make the final deliveries. Existing studies have only considered the case of one truck and one drone. In this study
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Data envelopment analysis: From non-monotonic to monotonic scale elasticities Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-15 Andreas Dellnitz, Madjid Tavana
The concept of returns to scale (RTS) or local scale elasticities in data envelopment analysis (DEA)—stemming from variable returns to scale (VRS) technology—has been recently criticized because of its misbehavior in the case of decreasing returns to scale (DRS). Here, the instrument should imply a downsizing force for improving productivity. In classical VRS technologies, however, it can hide respective
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Condition-based reallocation and maintenance for a 1-out-of-2 pairs balanced system Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-15 Xiaofei Chai, Onur A. Kilic, Jasper Veldman, Ruud H. Teunter, Xian Zhao
In a system consisting of multiple functionally exchangeable units, differences in units’ degradation levels can significantly affect the system’s performance. Dynamic reallocation of these units can improve performance and prolong the lifetime of the system. This study is the first to quantify the benefit of incorporating reallocation into a condition-based maintenance framework for a 1-out-of-2 pairs
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Discrete forecast reconciliation Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-14 Bohan Zhang, Anastasios Panagiotelis, Yanfei Kang
This paper presents a formal framework and proposes algorithms to extend forecast reconciliation to discrete-valued data, including low counts. A novel method is introduced based on recasting the optimisation of scoring rules as an assignment problem, which is solved using quadratic programming. The proposed framework produces coherent joint probabilistic forecasts for count hierarchical time series
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A congested facility location problem with strategic customers Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-13 Ata Jalili Marand, Pooya Hoseinpour
This study addresses a user-equilibrium congested facility location problem with delay-, accessibility-, and price-sensitive customers. A profit-maximizing service provider first makes location, service rate, and pricing decisions, and then strategic customers decide which facilities to patronize (if any). By incorporating the customers’ choice behavior as a set of equilibrium constraints into the
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Pricing and Capacity Allocation in Opaque Selling Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-12 Zihao Zhang, Mengying Zhang
To solve the supply and demand mismatch problem, intermediaries have emerged as an opaque channel for service providers to dispose of leftover capacity. This paper focuses on pricing and capacity allocation in opaque selling. We develop a Stackelberg game model, where two capacity-constrained service providers first decide the capacity allocated to an intermediary who then determines the opaque price
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Solving large-scale electricity market pricing problems in polynomial time Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-11 Mete Şeref Ahunbay, Martin Bichler, Teodora Dobos, Johannes Knörr
In centralized wholesale electricity markets worldwide, market operators use mixed-integer linear programming to solve the allocation problem. Prices are typically determined based on the duals of relaxed versions of this optimization problem. The resulting outcomes are efficient, but market operators must pay out-of-market uplifts to some market participants and incur a considerable budget deficit
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How power structure and markup schemes impact supply chain channel efficiency under price-dependent stochastic demand Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-10 Eunji Lee, Stefan Minner
Although considerable attention has been separately given to factors such as power structures, price-dependent demand, and markup pricing schemes, there has been limited exploration of the combined effects of these factors on supply chain efficiency and the leader’s advantage. We propose a game theoretic model in which a manufacturer sells a single product to a newsvendor retailer who sets both optimal
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The future of transport: Coordination in a new field between public and private transport Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-10 Hillel Bar-Gera, Marco Bijvank, Florian Jaehn, Simone Neumann, Sandra Transchel
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A disaggregated integer L-shaped method for stochastic vehicle routing problems with monotonic recourse Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-09 Lucas Parada, Robin Legault, Jean-François Côté, Michel Gendreau
This paper proposes a new integer L-shaped method for solving two-stage stochastic integer programs whose first-stage solutions can decompose into disjoint components, each one having a monotonic recourse function. In a minimization problem, the monotonicity property stipulates that the recourse cost of a component must always be higher or equal to that of any of its subcomponents. The method exploits
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Whitelisting versus advertising-recovery: Strategies to overcome advertising blocking by consumers Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-09 Ashutosh Singh, S. Sajeesh, Pradeep Bhardwaj
The significance of online advertising as a primary revenue stream for digital media cannot be understated. However, the rising adoption of ad-blocking software by users has adversely affected these revenues. In response to this challenge, digital publishers are exploring various strategies not only to maintain their revenues, but also to enhance them through online advertising, in addition to paid
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A generalized Benders decomposition approach for the optimal design of a local multi-energy system Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-05-09 Bingqian Liu, Côme Bissuel, François Courtot, Céline Gicquel, Dominique Quadri
A local multi-energy system (LMES) is a decentralized energy system producing energy under multiple forms to satisfy the energy demand of a set of buildings located in its neighborhood. We study the problem of optimally designing an LMES over a multi-phase horizon. This problem is formulated as a large-size mixed-integer linear program with a block-decomposable structure involving mixed-integer sub-problems