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The dynamic facility location problem with mobile production units: A waste recycling application Comput. Oper. Res. (IF 4.6) Pub Date : 2024-03-05 Eduardo Alarcon-Gerbier, Udo Buscher
This paper presents a multi-period location–production problem involving small recycling units that are embedded in standard containers and can, therefore, be relocated from site to site at short notice. The waste generated over time at different locations can be stored up to a specific limit, at which point recycling must occur. A mixed-integer program is implemented to plan the relocation of the
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A fast path relinking algorithm for the min–max edge crossing problem Comput. Oper. Res. (IF 4.6) Pub Date : 2024-03-04 Bo Peng, Lunwen Wu, Rafael Martí, Jiangshui Ma
The min–max edge crossing problem (MMECP) is a challenging and important problem arising in integrated-circuit design, information visualization, and software engineering. Drawing edges as straight lines in accordance with the hierarchical graph drawing standard, the goal is to reduce the maximum number of edge crossings in graphs. In this study, we propose a fast path relinking (FPR) method based
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Benchmarking problems for robust discrete optimization Comput. Oper. Res. (IF 4.6) Pub Date : 2024-03-04 Marc Goerigk, Mohammad Khosravi
Robust discrete optimization is a highly active field of research where a plenitude of combinations between decision criteria, uncertainty sets and underlying nominal problems are considered. Usually, a robust problem becomes harder to solve than its nominal counterpart, even if it remains in the same complexity class. For this reason, specialized solution algorithms have been developed. To further
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Model and metaheuristic for human–robot collaboration assembly line worker assignment and balancing problem Comput. Oper. Res. (IF 4.6) Pub Date : 2024-03-01 Zhaofang Mao, Yiting Sun, Kan Fang, Dian Huang, Jiaxin Zhang
Given the Industry 5.0 trend towards human-centric and resilient industries, workers continue to be considered as a valuable and irreplaceable resource. Human–robot collaboration (HRC) is a promising production mode that combines the advantages of both human workers and robots, resulting in improved productivity and reduced ergonomic risks for workers. In this study, we present one of the first attempts
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A variable neighborhood search approach for solving a real-world hierarchical multi-echelon vehicle routing problem involving HCT vehicles Comput. Oper. Res. (IF 4.6) Pub Date : 2024-03-01 Marduch Tadaros, Angelo Sifaleras, Athanasios Migdalas
This paper studies the Hierarchical Multi-Switch Multi-Echelon VRP (HMSME-VRP), a newly introduced VRP variant based on a real-world case involving High Capacity Vehicles (HCV). The problem originates from the policies of a distribution company in the Nordic countries where HCVs of up to 34.5 meters and up to 76 tons are allowed. The HMSME-VRP offer a new way to model distribution problems to cover
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A proactive aircraft recovery approach based on airport spatiotemporal network supply and demand coordination Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-29 Haipei Zang, Jinfu Zhu, Qi Zhu, Qiang Gao
The Aircraft Recovery Problem (ARP) is to modify the flight and aircraft schedules with compensation for the irregular aircraft operations due to disruptions, falling under passive control. This reactive approach is challenging and often leads to additional secondary delays. The accumulation of historical data and advancements in big data technology have enabled a proactive approach to ARP. If the
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Heuristic and metaheuristic procedures for the Parallel Assembly Lines Balancing Problem with multi-line workstations and buffer sizing Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-27 Harry Aguilar, Alberto García-Villoria, Rafael Pastor
This paper addresses the parallel assembly lines balancing problem (PALBP) with multi-line workstations, lines with different cycle times and buffer sizing. When a PALB system works with lines with different cycle times, the lines with multi-line workstations have to produce in batches; thus, the use of buffers may be needed. For the first time in the literature, this study jointly solved the PALBP
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Reentrant open shop scheduling problem with time lags and no-wait constraints Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-24 Kenza Alioui, Karim Amrouche, Mourad Boudhar
In this work, we consider the two-machine reentrant open shop scheduling problem with no-wait and exact time lags constraints. The objective is to minimize the makespan. We first prove that this problem is NP-hard in the strong sense, then we provide some polynomial sub-problems. To solve the general problem, a heuristic and metaheuristics with hybridizations are proposed with numerical experiments
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Supplier selection under disruption risk with hybrid procurement Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-23 Shakiba Enayati, Osman Y. Özaltın
In today’s global landscape, supply chains face a plethora of risks due to the increasingly dynamic and turbulent business environment. In this study, we introduce a supplier selection model with hybrid procurement under disruption risk. Specifically, we consider the supplier selection problem of a firm with multiple units (or business segments) demanding several products, raw materials, and services
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A comparison of alternative models for solving a non-linear single plant Hydro Unit Commitment problem Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-23 Alexandre Heintzmann, Christian Artigues, Pascale Bendotti, Sandra Ulrich Ngueveu, Cécile Rottner
A wide range of real world optimization problems involves continuous decisions and non-linearities. Each non-linear component of such problems can be modeled either linearly or non-linearly, considering or not additional integer variables. This results into different modeling choices that can drastically impact the solution time and quality. In this paper, we evaluate representative modeling alternatives
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A ride time-oriented scheduling algorithm for dial-a-ride problems Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-23 Claudia Bongiovanni, Nikolas Geroliminis, Mor Kaspi
This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theory, aims at finding minimal user ride time schedules in worst-case quadratic time. The algorithm can either return feasible routes or it can return
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A parallel variable neighborhood search for α-neighbor facility location problems Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-23 Guilherme O. Chagas, Luiz A.N. Lorena, Rafael D.C. dos Santos, Jacques Renaud, Leandro C. Coelho
In this paper, we employ the to develop a Parallel Variable Neighborhood Search (VNS) algorithm for the -neighbor -center problem (NCP) and the -neighbor -median problem (NMP). The NCP and the NMP are generalizations of the -center (CP) and -median (MP) problems, respectively. In the -neighbor problems, one seeks to open facilities and assign each of the customers to their closest ones. The objective
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Nesting and scheduling optimization of additive manufacturing systems: Mapping the territory Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-22 Marcelo Pinto, Cristóvão Silva, Matthias Thürer, Samuel Moniz
The application of Additive Manufacturing (AM) within industrial settings brings new challenges to operational research. This paper provides in-depth analyses of nesting and scheduling problems in the context of AM. Using bibliometric and systematic review methods, we map the progression of knowledge in this territory and provide a detailed characterization of the existing mathematical models and approaches
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Solving unconstrained binary polynomial programs with limited reach: Application to low autocorrelation binary sequences Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-22 Jens Vinther Clausen, Yves Crama, Richard Lusby, Elisabeth Rodríguez-Heck, Stefan Ropke
Unconstrained Binary Polynomial Programs (UBPs) are a class of optimization problems relevant in a broad array of fields. In this paper, we examine an example from communication engineering, namely low autocorrelation binary sequences and propose a new dynamic programming approach that is particularly effective on UBP instances that have a limited so-called reach, which is a metric that states the
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Shore hydrogen deployment problem in green ports Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-15 Qian Zhang, Zheyi Tan, Shuaian Wang, Lu Zhen
In the context of carbon neutrality and peak carbon, research on emerging technologies for the clean, efficient, safe, and sustainable development of green ports and green shipping is crucial. The application of carbon-free hydrogen fuel cell technology to vessels and ports is seen as an effective solution. This study investigates the deployment of shore hydrogen in a green port, aiming to optimize
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A comparative study of alternative formulations for the periodic vehicle routing problem Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-13 Saeedeh Ahmadi Basir, Güvenç Şahin, Gizem Özbaygın
This study investigates the periodic vehicle routing problem (PVRP) and its variant with time windows with a particular focus on alternative formulation approaches that can be solved by a state-of-the-art commercial solver. We propose a new vehicle flow formulation for the PVRP and strengthen it with valid inequalities. We also investigate two prominent formulations for the PVRP available in the literature:
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The Impact of Partial Production Capacity Sharing via Production as a Service Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-12 Christina J. Liepold, Okan Arslan, Gilbert Laporte, Maximilian Schiffer
Cloud manufacturing, one of the trends subsumed under Industry 4.0, influences industrial production settings as it transforms resource utilization into a shared on-demand service. Central to cloud manufacturing is the Production as a Service (PaaS) paradigm, which allows intermediaries to coordinate supply and demand of idle production capacities and enables collaboration in production through outsourcing
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The costs of overcrowding (and release): Strategic discharges for isolated facilities during epidemiological outbreaks Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-10 Kati Moug, Siqian Shen
For isolated, densely populated facilities, such as prisons and nursing homes, it is difficult to enact social distancing measures when catastrophic epidemiological outbreaks occur. In such facilities, strategic releases can enhance social distancing, yet have inherent costs, e.g., the potential for recidivism in crime for prisons, or the financial cost of incentives for residents to break contracts
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An improved column-generation-based matheuristic for learning classification trees Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-10 Krunal Kishor Patel, Guy Desaulniers, Andrea Lodi
Decision trees are highly interpretable models for solving classification problems in machine learning (ML). The standard ML algorithms for training decision trees are fast but generate suboptimal trees in terms of accuracy. Other discrete optimization models in the literature address the optimality problem but only work well on relatively small datasets. Firat et al. (2020) proposed a column-generation-based
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Optimal-transport satisficing with applications to capacitated hub location Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-09 Jie Hu, Tianqi Liu, Zhi Chen, Shuming Wang
We present a coherent satisficing criterion for evaluating the attractiveness of strategic decisions under uncertainty. Specifically, we define a satisficing criterion using the optimal-transport measure, termed as Optimal-Transport Satisficing (OTS), to evaluate the random cost saving (that equals cost target minus cost) associated with a strategic decision. We apply this criterion to the capacitated
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Improving the scheduling of railway maintenance projects by minimizing passenger delays subject to event requests of railway operators Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-08 Y.R. de Weert, K. Gkiotsalitis, E.C. van Berkum
In the Netherlands, it is expected that passenger activities on railway networks will double by 2050. To manage the passenger demand, railway capacity planning needs to be adapted. One fundamental aspect of the railway capacity planning is the scheduling of large maintenance projects. These maintenance requests should not be scheduled during major events to avoid the disruption of service. To do so
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General Variable Neighborhood Search for the optimization of software quality Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-08 Javier Yuste, Eduardo G. Pardo, Abraham Duarte
In the area of Search-Based Software Engineering, software engineering issues are formulated and tackled as optimization problems. Among the problems within this area, the Software Module Clustering Problem (SMCP) consists of finding an organization of a software project that minimizes coupling and maximizes cohesion. Since modular code is easier to understand, the objective of this problem is to increase
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Optimal resource allocation and routing in robotic mobile fulfillment systems Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-08 Saeedeh Hashemi, Mohammad Ranjbar
This paper addresses a combinatorial optimization problem in the context of a robotic mobile fulfillment system deployed in a warehouse that consists of movable racks, a picker, and a fleet of mobile robots. The objective is to efficiently prepare a set of orders with specified due dates by bringing the racks to a picking station in a sequential manner, where the picker selects the required products
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Reducing the feasible solution space of resource-constrained project instances Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-07 Mario Vanhoucke, José Coelho
This paper present an instance transformation procedure to modify known instances of the resource-constrained project scheduling problem to make them easier to solve by heuristic and/or exact solution algorithms. The procedure makes use of a set of transformation rules that aim at reducing the feasible search space without excluding at least one possible optimal solution. The procedure will be applied
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Robust optimization for a steel production planning problem with uncertain demand and product substitution Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-07 Gongshu Wang, Jing Wu, Yang Yang, Lijie Su
This paper addresses a production planning problem in the steel industry, specifically focusing on determining production quantities and product-to-order assignment considering uncertain demand and product substitution. For the deterministic scenario, we formulate the problem as a mixed integer programming model to effectively represent its combinatorial nature. For uncertain scenarios, we develop
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A parallel branch-and-bound heuristic for the integrated long-haul and local vehicle routing problem on an adaptive transportation network Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-05 Junko Hosoda, Stephen J. Maher, Yuji Shinano, Jonas Christoffer Villumsen
Consolidation of commodities and coordination of vehicle routes are fundamental features of supply chain management problems. While locations for consolidation and coordination are typically known a priori, in adaptive transportation networks this is not the case. The identification of such consolidation locations forms part of the decision making process. Supply chain management problems integrating
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Model formulations for pickup and delivery problems in designated driver services Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-30 Alp Arslan, Niels Agatz, F. Jordan Srour
Designated driver services use company vehicles to deliver drivers to customers. The drivers then drive the customers from their origins to their destinations in the customers’ own cars; at the destinations, the drivers are picked up by a company vehicle. We typically see teams of drivers assigned to company vehicles serving customers. However, when the drivers may be dropped off by one vehicle and
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Exact and heuristic solution approaches for the Generalized Independent Set Problem Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-30 Mingming Zheng, Jin-Kao Hao, Qinghua Wu
The generalized independent set problem (GIS) is a generalization of the classical maximum independent set problem and has various practical applications, such as forest harvesting and image/video processing. In this work, we present highly effective exact and heuristic algorithms for the GIS. In the proposed exact algorithm, a new upper bound on the maximum net benefit of an independent set in a subgraph
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Minimizing passenger waiting time in the multi-route bus fleet allocation problem through distributionally robust optimization and reinforcement learning Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-02 Xiang Li, Xiaojie An, Bowen Zhang
Public buses serve a vital role in urban transportation systems by alleviating traffic congestion, reducing carbon emissions, and providing cost-effective and accessible travel options. Nonetheless, a noticeable mismatch frequently exists between the supply and demand for bus services, leading to reduced passenger satisfaction in reality, especially in suburban areas. To tackle this problem, our study
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The pollution-routing problem with speed optimization and uneven topography Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-02 David Lai, Yasel Costa, Emrah Demir, Alexandre M. Florio, Tom Van Woensel
This paper considers a joint pollution-routing with time windows and speed optimization problem (PRP-SO) where vehicle speed, payload, and road grade influence fuel costs and emissions. We present two advanced optimization methods (i.e., approximate and exact) for solving the PRP-SO. The approximate strategy solves large-scale instances of the problem with a Tabu search-based metaheuristic coupled
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Multi-period fourth-party logistics network design with the temporary outsourcing service under demand uncertainty Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-01 Mingqiang Yin, Min Huang, Dazhi Wang, Shu-Cherng Fang, Xiaohu Qian, Xingwei Wang
In this paper, a novel multi-period fourth party logistics (4PL) network design problem integrating the temporary outsourcing service under demand uncertainty is studied, in which the temporary outsourcing strategy is proposed to accommodate uncertain demand overflows. To address this problem, a two-stage stochastic programming model is formulated. Using the Latin hypercube sampling approach, a mixed
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Routing one million customers in a handful of minutes Comput. Oper. Res. (IF 4.6) Pub Date : 2024-02-01 Luca Accorsi, Daniele Vigo
This paper proposes a new dataset of Capacitated Vehicle Routing Problem instances, up to two orders of magnitude larger than those in the currently used benchmarks. Although these sizes might not have an immediate application to real-world logistic scenarios, we believe they could foster fresh new research efforts on the design of effective and efficient algorithmic components for routing problems
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A discrete group teaching optimization algorithm for solving many-objective sand casting whole process production scheduling problem Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-28 Hongtao Tang, Wei Zhang, Xixing Li, Shupeng Wei
Hybrid flowshop scheduling is widely used in various industrial manufacturing areas, particularly in the production of castings. The parallel processes in the mold manufacturing stage and the single batch coupled processes in the melting and casting and post-processing stages make the model more complex. Firstly, a multi-stage hybrid flowshop scheduling model is constructed to minimize makespan, machine
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Optimizing high-speed railway express system under uncertainty Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-30 Lu Zhen, Xueting He, Nianzu Zhang, Zhiyuan Yang, Yiran Ren
The rapid expansion of high-speed railway (HSR) networks has elevated the HSR express system, which combines road and HSR transport, as a notable intermodal transport choice. This research delves into the optimization challenges present in the HSR express system's operation, given the unpredictable freight demands. These challenges encompass vehicle arrangement, station selection, freight allocation
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Exact solution method for vehicle-and-drone cooperative delivery routing of blood products Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-24 Yunqiang Yin, Ling Qing, Dujuan Wang, T.C.E. Cheng, Joshua Ignatius
Blood products, such as platelets, play a major role in saving and maintaining lives, and preventing and treating diseases, which need timely delivery. To achieve cost-efficient and fast deliveries, integrating unmanned aerial vehicles (or drones) into blood product distribution network design provides a competitive advantage, which however increases the operational challenges. We address the vehicle-and-drone
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A surrogate-based heuristic for production planning problem of orders in small foundries Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-24 Giovanna Abreu Alves, Iago Pinheiro de Freitas, Victor Claudio Bento Camargo
Market foundry production processes are characterized by raw materials that feed a furnace that produces metal alloys with limited capacity to meet item order demand. The foundry production system considered here is make-to-order. Although in the literature, production planning does not usually consider items produced as belonging to orders, it is essential to address this specificity. All component
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Multi-objective search game: Long-term vs short-term Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-20 Florian Delavernhe
This study focuses on investigating a multi-objective search allocation game problem, specifically addressing the distribution of a search budget (player 1) across a searched area to detect an evading target (player 2). The game is defined as a two-person zero-sum game, as an optimal search strategy must consider the target’s optimal evasion strategy. Traditionally, the sole objective function in search
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Modeling and solving the two-level generalized median tour problem Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-22 Carlos Obreque, Germán Paredes-Belmar, Pablo A. Miranda-Gonzalez, Giovanni Campuzano, Gabriel Gutiérrez-Jarpa
In many real-world situations, the beneficiaries of a distribution system may be grouped into clusters, requiring a transportation structure to serve each cluster of beneficiaries efficiently. For instance, in public services, such as health, education, and emergencies, delivery tasks rely on the local authority of each district or cluster. In this context, a two-level distribution system named the
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The integrated on-demand bus routing problem: Combining on-demand buses with a high-frequency fixed line public transport network Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-20 Lissa Melis, Michell Queiroz, Kenneth Sörensen
In this work we analyze the performance of integrating a large-scale on-demand bus system with a high-frequency fixed line public transport network in an urban context. Given are a high-speed metro network, a set of real-time requests, a set of bus station locations and a fleet of fixed capacity minibuses. Requests have a set of possible departure/arrival bus stations within walking distance of the
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The stochastic share-a-ride problem with electric vehicles and customer priorities Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-20 Yutong Gao, Shu Zhang, Zhiwei Zhang, Quanwu Zhao
We introduce a stochastic share-a-ride problem in which a fleet of electric vehicles (EV) in a ride-hailing system are dynamically dispatched to serve passenger and parcel orders in a shared manner. We assume uncertain demands of both passenger and parcel orders and consider that passenger orders have priority over parcel orders. Passengers must be transported directly from their origins to destinations
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Routing and scheduling of platform supply vessels in offshore oil and gas logistics Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-23 Victor A. Silva, Akang Wang, Virgílio José Martins Ferreira Filho, Chrysanthos E. Gounaris
In this work, we focus on an operational logistics problem that arises in the offshore oil and gas exploration and production industry. In particular, we aim to design cost-effective routes and schedules for platform supply vessels, which are routinely employed to deliver necessary supplies to the platforms as well as to collect from those platforms used materials that need to be transported back to
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Learning driven three-phase search for the maximum independent union of cliques problem Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-23 Zhi Lu, Jian Gao, Jin-Kao Hao, Pingle Yang, Lixin Zhou
Given a simple and undirected graph, the maximum independent union of cliques (IUC) problem aims to identify a subset of vertices with maximum cardinality, such that each connected component of the induced subgraph is a complete graph. As a generalization of the popular NP-hard maximum clique problem, the maximum IUC problem is of great practical importance for social network analysis and network-based
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Deep clustering of the traveling salesman problem to parallelize its solution Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-18 Vadim V. Romanuke
A method of heuristically solving large traveling salesman problems is suggested, where a dramatic computational speedup is guaranteed. A specific genetic algorithm is the solver. The initial problem is broken into a set of open-loop subproblems by clustering the nodes. First, the nodes are broken into just two clusters. If these open-loop subproblems are tractable and can be solved within reasonable
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Delay-resistant robust vehicle routing with heterogeneous time windows Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-17 Lukas Metz, Petra Mutzel, Tim Niemann, Lukas Schürmann, Sebastian Stiller, Andreas M. Tillmann
We consider a robust variant of the vehicle routing problem with heterogeneous time windows (RVRP-HTW) with a focus on delay-resistant solutions. Here, customers have different availability time windows for every vehicle and must be provided with a preferably tight appointment window for the planned service. Different vehicles are a possibility to model different days on which one physical vehicle
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Scheduling identical serial-batching machines in the engine manufacturing supply chain by an integrated variable neighborhood search algorithm Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-19 Shaojun Lu, Chongyao Ma, Xinbao Liu, Panos M. Pardalos
The optimization of the high-end equipment manufacturing process is becoming progressively more difficult, which brings a big challenge for high-end equipment manufacturers. Numerous variables, such as equipment wear and tear, the service level of the supply chain, etc., may have a significant impact on the efficiency of high-end equipment manufacturing. In this paper, motivated by the need to improve
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Planning container inspection and repair: A case study Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-18 Mikhail Y. Kovalyov, Katarzyna A. Kuzmicz, Mikhail N. Lukashevich, Erwin Pesch
The aim of this paper is to introduce a real-life problem of optimal planning of container inspection and repair on several facilities over several time periods assuring effective supply of empty containers indispensable for seamless global maritime transportation. The containers are of several types and quality levels. The objective is to minimize the total holding, inspection, repair, transportation
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Efficient optimization in stochastic production planning problems with product substitution Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-09 Shing Chih Tsai, Yingchieh Yeh, Honggang Wang, Tsung Ching Chou
We consider the stochastic production planning problem with product substitution, which can be decomposed into several optimization subproblems with sequential decisions. The decision variables in each time period include (1) the product substitution decision and (2) the recipe input quantity decision. The goal is to minimize the total of production cost, holding cost, and shortage cost, while achieving
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Re-use of samples in stochastic annealing Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-14 Robin Ball, Juergen Branke, Stephan Meisel
The re-use of samples in stochastic black box optimisation is a double-edged sword. On the one hand it has the potential of substantially reducing the number of simulation runs required, on the other hand it introduces dependencies between iterations of the optimisation algorithm that may misguide the search. This paper proposes a principled way to re-use samples in stochastic annealing, a generalisation
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Simulation-based variable neighborhood search for optimizing skill assignments in multi-server facilities with inventories Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-12 Moustafa Abdelwanis, Adriana F. Gabor, Nenad Mladenovic, Andrei Sleptchenko
This paper addresses the joint optimization problem of skill assignments and inventory in a multi-skill, multi-server repair facility. Failures of different part types occur according to Poisson processes, and each part type requires a certain repair skill. The repair facility supplies ready-to-install spare parts when available in the inventory, according to the (S−1,S) inventory policy. The repair
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Logic-based Benders decomposition for bi-objective parallel machine selection and job scheduling with release dates and resource consumption Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-11 Peng Wu, Yun Wang, Chengbin Chu
This work addresses a new bi-objective parallel machine selection and job scheduling problem with release dates and resource consumption. It consists in optimally selecting subcontractors (machines) from a set of geographically dispersed locations and scheduling the orders (jobs) to the selected subcontractors for processing while meeting the order release dates and resource consumption restrictions
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Combinatorial Benders decomposition for the operational aircraft maintenance routing problem Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-11 Emine Es Yurek
The operational aircraft maintenance routing problem (OAMRP) assigns the aircraft in a fleet to scheduled flights while satisfying maintenance requirements. Aviation rules enforce the aircraft to undergo maintenance before the maximum accumulated flight hour is exceeded. Due to the dynamic environment of the airline industry, aircraft routes considering operational requirements become definite a few
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Unified Branch-and-Benders-Cut for two-stage stochastic mixed-integer programs Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-08 Arthur Mahéo, Simon Belieres, Yossiri Adulyasak, Jean-François Cordeau
Two-stage stochastic programs are a class of stochastic problems where uncertainty is discretized into scenarios, making them amenable to solution approaches such as Benders decomposition. However, classic Benders decomposition is not applicable to general two-stage stochastic mixed-integer programs due to the restriction that the second-stage variables should be continuous. We propose a novel Benders
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A Lagrangian relaxation algorithm for stochastic fixed interval scheduling problem with non-identical machines and job classes Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-08 Martin Branda, Monika Matoušková
This paper deals with operational fixed interval scheduling problems under uncertainty caused by random delays. This stochastic programming problem has a deterministic reformulation based on network flow under the assumption that the machines are identical and the multivariate distribution of random delays follows an Archimedean copula. In this paper, we focus on the problem with heterogeneous machines
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A modified variable neighborhood search algorithm for dynamic lot-sizing with supplier selection under varying delivery time quotation Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-05 Fangjun Zhu, Jun Pei, Baoyu Liao, Ya Zhou, Panos M. Pardalos
This paper investigates a dynamic lot-sizing problem with supplier selection, where the manufacturer develops an aggregate plan to meet product delivery demand with the objective of minimizing the cost. Specifically, a novel supplier selection scenario with varying delivery time quotation is considered, i.e., the manufacturer places raw material replenishment orders with varying delivery time quotation
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Revised eight-step feasibility checking procedure with linear time complexity for the Dial-a-Ride Problem (DARP) Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-05 Somayeh Sohrabi, Koorush Ziarati, Morteza Keshtkaran
In the context of Dial-a-Ride Problems (DARPs), the eight-step feasibility checking procedure is one of the most commonly used methods. The time complexity of this procedure is considered as O(n2) in the literature. In this study, a version of this procedure is proposed with O(nlogQ) time complexity. Since, in DARPs, the capacity of each vehicle is a small constant, the method introduced in this paper
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An adaptive variable neighbourhood search approach for the dynamic vehicle routing problem Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-05 Jeeu Fong Sze, Said Salhi, Niaz Wassan
In the traditional vehicle routing problem (VRP), a route plan is pre-determined and remains unchanged afterwards. However in practice, several unforeseen events could occur at any point, which cause traffic congestion and delay to the original planned routes. It is therefore important to re-optimise the routes by taking into consideration the real-time information, leading to the Dynamic VRP (DVRP)
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An efficient solution space exploring and descent method for packing equal spheres in a sphere Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-04 Jianrong Zhou, Shuo Ren, Kun He, Yanli Liu, Chu-Min Li
The problem of packing equal spheres in a spherical container is a classic global optimization problem, which has attracted enormous studies in academia and found various applications in industry. This problem is computationally very challenging, and many efforts focus on small-scale instances with the number of spherical items less than 200 in the literature. In this work, we propose an efficient
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Algorithms and computational study on a transportation system integrating public transit and ridesharing of personal vehicles Comput. Oper. Res. (IF 4.6) Pub Date : 2024-01-03 Qian-Ping Gu, Jiajian Leo Liang
The potential of integrating public transit with ridesharing includes shorter travel time for commuters and higher occupancy rate of personal vehicles and public transit ridership. In this paper, we describe a centralized transit system that integrates public transit and ridesharing to reduce travel time for commuters. In the system, a set of ridesharing providers (drivers) and a set of public transit