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Heuristic reoptimization of time‐extended multi‐robot task allocation problems Networks (IF 2.1) Pub Date : 2024-03-12 Esther Bischoff, Saskia Kohn, Daniela Hahn, Christian Braun, Simon Rothfuß, Sören Hohmann
Providing high quality solutions is crucial when solving NP‐hard time‐extended multi‐robot task allocation (MRTA) problems. Reoptimization, that is, the concept of making use of a known solution to an optimization problem instance when the solution to a similar problem instance is sought, is a promising and rather new research field in this application domain. However, so far no approximative time‐extended
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New approximations for network reliability Networks (IF 2.1) Pub Date : 2024-03-04 Jason I. Brown, Theodore Kolokolnikov, Robert E. Kooij
We introduce two new methods for approximating the all‐terminal reliability of undirected graphs. First, we introduce an edge removal process: remove edges at random, one at a time, until the graph becomes disconnected. We show that the expected number of edges thus removed is equal to , where is the number of edges in the graph, and is the average of the all‐terminal reliability polynomial. Based
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Solving the probabilistic drone routing problem: Searching for victims in the aftermath of disasters Networks (IF 2.1) Pub Date : 2024-02-13 Amadeu Almeida Coco, Christophe Duhamel, Andréa Cynthia Santos, Matheus Nohra Haddad
Several major industrial disasters happen each year around the world. They usually involve limited accessibility, poor ground conditions, and toxic wastes. As a consequence, this reduces the efficiency of humanitarian operations. In such a context, flying drones may be a viable alternative: faster, no dependency on ground conditions, and larger areas scanned. They are also better suited for following
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Enhanced methods for the weight constrained shortest path problem Networks (IF 2.1) Pub Date : 2024-02-13 Saman Ahmadi, Guido Tack, Daniel Harabor, Philip Kilby, Mahdi Jalili
The classic problem of constrained pathfinding is a well-studied, yet challenging, network optimization problem with a broad range of applications in various areas such as communication and transportation. The weight constrained shortest path problem (WCSPP), the base form of constrained pathfinding with only one side constraint, aims to plan a cost-optimum path with limited weight/resource usage.
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Virtual network function reconfiguration in 5G networks: An optimization perspective Networks (IF 2.1) Pub Date : 2024-02-08 Hanane Biallach, Mustapha Bouhtou, Kristina Kumbria, Dritan Nace, Artur Tomaszewski
One of the major challenges in managing 5G networks is the reconfiguration of network slices. The task covers in particular reconfiguration and relocation of virtual network functions (VNFs) so as to match the service requirements of the slices and the availability of resources of the data centers. In this article, we study in deep the problem of optimal VNFs reconfiguration analyzing a number of its
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An improved hybrid genetic search with data mining for the CVRP Networks (IF 2.1) Pub Date : 2024-02-08 Marcelo Rodrigues de Holanda Maia, Alexandre Plastino, Uéverton dos Santos Souza
The hybrid genetic search (HGS) metaheuristic has produced outstanding results for several variants of the vehicle routing problem. A recent implementation of HGS specialized to the capacitated vehicle routing problem (CVRP) is a state-of-the-art method for this variant. This paper proposes an improved HGS for the CVRP obtained by incorporating a new solution generation method into its (re-)initialization
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Integrated commercial and operations planning model for schedule design, aircraft rotation and crew scheduling in airlines Networks (IF 2.1) Pub Date : 2024-01-23 Ankur Garg, Yogesh Agarwal, Rajiv Kumar Srivastava, Suresh Kumar Jakhar
The commercial and operations planning in airlines has traditionally been a hierarchical process starting with flight schedule design, followed by fleet assignment, aircraft rotation planning and finally the crew scheduling. The hierarchical planning approach has a drawback that the optimal solution for a planning phase higher in hierarchy may either be infeasible for the subsequent phase or may lead
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Algorithms and complexity for the almost equal maximum flow problem Networks (IF 2.1) Pub Date : 2024-01-23 Rebekka Haese, Till Heller, Sven O. Krumke
In the equal maximum flow problem (EMFP), we aim for a maximum flow where we require the same flow value on all arcs in some given subsets of the arc set, so called homologous arc sets. In this article, we study the closely related almost equal maximum flow problems (AEMFP) where the flow values on arcs of one homologous arc set differ at most by the valuation of a so called deviation function Δ$$
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On the complexity of the upgrading version of the maximal covering location problem Networks (IF 2.1) Pub Date : 2024-01-17 Marta Baldomero-Naranjo, Jörg Kalcsics, Antonio M. Rodríguez-Chía
In this article, we study the complexity of the upgrading version of the maximal covering location problem with edge length modifications on networks. This problem is NP-hard on general networks. However, in some particular cases, we prove that this problem is solvable in polynomial time. The cases of star and path networks combined with different assumptions for the model parameters are analysed.
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Shortest path network interdiction with asymmetric uncertainty Networks (IF 2.1) Pub Date : 2024-01-15 She'ifa Z. Punla-Green, John E. Mitchell, Jared L. Gearhart, William E. Hart, Cynthia A. Phillips
This paper considers an extension of the shortest path network interdiction problem that incorporates robustness to account for parameter uncertainty. The shortest path interdiction problem is a game of two players with conflicting agendas and capabilities: an evader, who traverses the arcs of a network from a source node to a sink node using a path of shortest length, and an interdictor, who maximizes
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Special cases of the minimum spanning tree problem under explorable edge and vertex uncertainty Networks (IF 2.1) Pub Date : 2024-01-11 Corinna Mathwieser, Eranda Çela
This article studies the Minimum Spanning Tree Problem under Explorable Uncertainty as well as a related vertex uncertainty version of the problem. We particularly consider special instance types, including cactus graphs, for which we provide randomized algorithms. We introduce the problem of finding a minimum weight spanning star under uncertainty for which we show that no algorithm can achieve constant
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How vulnerable is an undirected planar graph with respect to max flow Networks (IF 2.1) Pub Date : 2024-01-03 Lorenzo Balzotti, Paolo G. Franciosa
We study the problem of computing the vitality of edges and vertices with respect to the st$$ st $$-max flow in undirected planar graphs, where the vitality of an edge/vertex is the st$$ st $$-max flow decrease when the edge/vertex is removed from the graph. This allows us to establish the vulnerability of the graph with respect to the st$$ st $$-max flow. We give efficient algorithms to compute
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Math-based reinforcement learning for the adaptive budgeted influence maximization problem Networks (IF 2.1) Pub Date : 2023-12-26 Edoardo Fadda, Evelina Di Corso, Davide Brusco, Vlad Stefan Aelenei, Alexandru Balan Rares
In social networks, the influence maximization problem requires selecting an initial set of nodes to influence so that the spread of influence can reach its maximum under certain diffusion models. Usually, the problem is formulated in a two-stage un-budgeted fashion: The decision maker selects a given number of nodes to influence and observes the results. In the adaptive version of the problem, it
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Generalizing Horn's conditions for preemptive scheduling on identical parallel machines via network flow techniques Networks (IF 2.1) Pub Date : 2023-12-20 Akiyoshi Shioura, Vitaly A. Strusevich, Natalia V. Shakhlevich
We study the use of flow-based algorithmic and proof techniques applied to preemptive scheduling of jobs on parallel identical machines. For the classical problem in which the jobs have individual release dates and must be finished by a common deadline, we present and prove unified necessary and sufficient conditions for the existence of a feasible schedule by examining the structure of minimum cuts
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Learning to repeatedly solve routing problems Networks (IF 2.1) Pub Date : 2023-12-14 Mouad Morabit, Guy Desaulniers, Andrea Lodi
In the last years, there has been a great interest in machine-learning-based heuristics for solving NP-hard combinatorial optimization problems. The developed methods have shown potential on many optimization problems. In this paper, we present a learned heuristic for the reoptimization of a problem after a minor change in its data. We focus on the case of the capacited vehicle routing problem with
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Asymptotic bounds for clustering problems in random graphs Networks (IF 2.1) Pub Date : 2023-12-13 Eugene Lykhovyd, Sergiy Butenko, Pavlo Krokhmal
Graph clustering is an important problem in network analysis. This problem can be approached by first finding a large cluster subgraph (i.e., a subgraph in which every connected component is a complete graph), perhaps in a relaxed form (connected components may have missing edges), and then assigning each of the remaining vertices to one of the connected components of the cluster subgraph according
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The complexity landscape of disaster-aware network extension problems Networks (IF 2.1) Pub Date : 2023-12-12 Balázs Vass, Beáta Éva Nagy, Balázs Brányi, János Tapolcai
This article deals with the complexity of problems related to finding cost-efficient, disaster-aware cable routes. We overview various mathematical problems studied to augment a backbone network topology to make it more robust against regional failures. These problems either consider adding a single cable, multiple cables, or even nodes too. They adapt simplistic or more sophisticated regional failure
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Maximizing SDN resilience to node-targeted attacks through joint optimization of the primary and backup controllers placements Networks (IF 2.1) Pub Date : 2023-12-06 Michał Pióro, Mariusz Mycek, Artur Tomaszewski, Amaro de Sousa
In software defined networks (SDN) packet data switches are configured by a limited number of SDN controllers, which respond to queries for packet forwarding decisions from the switches. To enable optimal control of switches in real time the placement of controllers at network nodes must guarantee that the controller-to-controller and switch-to-controller communications delays are bounded. Apart from
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Solving the routing and spectrum assignment problem, driven by combinatorial properties Networks (IF 2.1) Pub Date : 2023-11-28 Pedro Henrique Fernandes da Silva, Hervé Kerivin, Juan Pablo Nant, Annegret K. Wagler
The routing and spectrum assignment problem in modern optical networks is an NP-hard problem that has received increasing attention during the last years. The majority of existing integer linear programming models for the problem uses edge-path formulations where variables are associated with all possible routing paths so that the number of variables grows exponentially with the size of the instance
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Topology reconstruction using time series data in telecommunication networks Networks (IF 2.1) Pub Date : 2023-11-28 David Pisinger, Siv Sørensen
We consider Hybrid fiber-coaxial (HFC) networks in which data is transmitted from a root node to a set of customers using a series of splitters and coaxial cable lines that make up a tree. The physical locations of the components in a HFC network are always known but frequently the cabling is not. This makes cable faults difficult to locate and resolve. In this study we consider time series data received
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Balancing graph Voronoi diagrams with one more vertex Networks (IF 2.1) Pub Date : 2023-11-21 Guillaume Ducoffe
Let G=(V,E)$$ G=\left(V,E\right) $$ be a graph with unit-length edges and nonnegative costs assigned to its vertices. Given a list of pairwise different vertices S=(s1,s2,…,sp)$$ S=\left({s}_1,{s}_2,\dots, {s}_p\right) $$, the prioritized Voronoi diagram of G$$ G $$ with respect to S$$ S $$ is the partition of G$$ G $$ in p$$ p $$ subsets V1,V2,…,Vp$$ {V}_1,{V}_2,\dots, {V}_p $$ so that, for every
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A hybrid genetic algorithm for the Hamiltonian p-median problem Networks (IF 2.1) Pub Date : 2023-11-20 Pengfei He, Jin-Kao Hao, Qinghua Wu
The Hamiltonian p-median problem consists of finding p(p$$ p $$ is given) non-intersecting Hamiltonian cycles in a complete edge-weighted graph such that each cycle visits at least three vertices and each vertex belongs to exactly one cycle, while minimizing the total cost of pcycles. In this work, we present an effective and scalable hybrid genetic algorithm to solve this computationally challenging
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A survivable variant of the ring star problem Networks (IF 2.1) Pub Date : 2023-11-10 Julien Khamphousone, Fabian Castaño, André Rossi, Sonia Toubaline
The Ring Star Problem consists in selecting a subset of nodes called hubs including the depot and linking them with a cycle, the remaining nodes being connected to exactly one hub, at minimum cost. We study a survivable variant of the Ring Star Problem where at most one node in a given subset of so-called uncertain nodes can fail if selected as a hub. We model this problem as an Integer Linear Program
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A continuous-time service network design and vehicle routing problem Networks (IF 2.1) Pub Date : 2023-11-07 Yun He, Mike Hewitt, Fabien Lehuédé, Juliette Medina, Olivier Péton
This paper considers the integrated planning of goods transportation through a multi-echelon supply chain consisting of a nationwide network and regional distribution system. The previously studied Service Network Design and Routing Problem considered similar planning decisions, albeit with multiple restrictions regarding the transportation of goods that can eliminate the opportunities for transportation
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The complexity of the timetable-based railway network design problem Networks (IF 2.1) Pub Date : 2023-10-12 Nadine Friesen, Tim Sander, Christina Büsing, Karl Nachtigall, Nils Nießen
Because of the long planning periods and their long life cycle, railway infrastructure has to be outlined long ahead. At the present, the infrastructure is designed while only little about the intended operation is known. Hence, the timetable and the operation are adjusted to the infrastructure. Since space, time and money for extension measures of railway infrastructure are limited, each modification
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Min–max optimization of node-targeted attacks in service networks Networks (IF 2.1) Pub Date : 2023-10-10 Bernard Fortz, Mariusz Mycek, Michał Pióro, Artur Tomaszewski
This article considers resilience of service networks that are composed of service and control nodes to node-targeted attacks. Two complementary problems of selecting attacked nodes and placing control nodes reflect the interaction between the network operator and the network attacker. This interaction can be analyzed within the framework of game theory. Considering the limited performance of the previously
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A rolling horizon framework for the time-dependent multi-visit dynamic safe street snow plowing problem Networks (IF 2.1) Pub Date : 2023-10-06 Georg E. A. Fröhlich, Margaretha Gansterer, Karl F. Doerner
As a major real-world problem, snow plowing has been studied extensively. However, most studies focus on deterministic settings with little urgency yet enough time to plan. In contrast, we assume a severe snowstorm with little known data and little time to plan. We introduce a novel time-dependent multi-visit dynamic safe street snow plowing problem and formulate it on a rolling-horizon-basis. To solve
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Last-mile delivery with drone and lockers Networks (IF 2.1) Pub Date : 2023-10-04 Marco Antonio Boschetti, Stefano Novellani
In this article, we define a new routing problem that arises in the last-mile delivery of parcels, in which customers can be served either directly at home by a capacitated truck, or possibly with a drone carried on the truck, or in a self-service mode using one of the available lockers. We investigate four different formulations, and for one of them, we propose a branch-and-cut approach. We also discuss
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Exact separation of the rounded capacity inequalities for the capacitated vehicle routing problem Networks (IF 2.1) Pub Date : 2023-09-29 Konstantin Pavlikov, Niels Christian Petersen, Jon Lilholt Sørensen
The family of Rounded Capacity (RC) inequalities is one of the most important sets of valid inequalities for the Capacitated Vehicle Routing Problem (CVRP). This paper considers the problem of separation of violated RC inequalities and develops an exact procedure employing mixed integer linear programming. The developed routine is demonstrated to be very efficient for small and medium-sized problem
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Decision support for the technician routing and scheduling problem Networks (IF 2.1) Pub Date : 2023-09-19 Mette Gamst, David Pisinger
The technician routing and scheduling problem (TRSP) optimizes routes for technicians serving tasks subject to qualifications, time constraints, and routing costs. In the literature, the TRSP is solved either to provide actual technician work schedules or to perform what-if analyses on different TRSP scenarios. A TRSP scenario consists of a given number of tasks, technicians, skills, working hours
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An iterated local search for a multi-period orienteering problem arising in a car patrolling application Networks (IF 2.1) Pub Date : 2023-09-15 Victor Hugo Vidigal Corrêa, Hang Dong, Manuel Iori, André Gustavo dos Santos, Mutsunori Yagiura, Giorgio Zucchi
This paper addresses a real-world multi-period orienteering problem arising in a large Italian company that needs to patrol an area in order to provide security services to a set of customers. Each customer requires different services on a weekly basis. Some services are mandatory, while others are optional. It might be impossible to perform all optional services, and each of them is assigned a score
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Yield uncertainty and strategic formation of supply chain networks Networks (IF 2.1) Pub Date : 2023-09-08 Victor Amelkin, Rakesh Vohra
To understand how supply uncertainty affects the structure of supply chain networks we consider a setting where retailers and suppliers must establish a costly relationship with each other prior too engaging in trade. Suppliers, with uncertain yield, announce wholesale prices, while retailers must decide which suppliers to link to based on their wholesale prices. Subsequently, retailers compete with
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A demand-responsive feeder service with a maximum headway at mandatory stops Networks (IF 2.1) Pub Date : 2023-09-07 Bryan David Galarza Montenegro, Kenneth Sörensen, Pieter Vansteenwegen
Public transportation out of suburban or rural areas is crucial. Feeder transportation services offer a solution by transporting passengers to areas where more options for public transport are available. On one hand, fully flexible demand-responsive feeder services (DRFSs) efficiently tailor their service to the needs of the passengers. On the other hand, traditional feeder services provide predictability
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Generalized nash fairness solutions for bi-objective minimization problems Networks (IF 2.1) Pub Date : 2023-09-03 Minh Hieu Nguyen, Mourad Baiou, Viet Hung Nguyen, Thi Quynh Trang Vo
In this article, we consider a particular case of bi-objective optimization (BOO), called bi-objective minimization (BOM), where the two objective functions to be minimized take only positive values. As well as for BOO, most of the methods proposed in the literature for solving BOM focus on computing the Pareto-optimal solutions representing different trade-offs between two objectives. However, it
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Robust transshipment problem under consistent flow constraints Networks (IF 2.1) Pub Date : 2023-08-31 Christina Büsing, Arie M. C. A. Koster, Sabrina Schmitz
In this article, we study robust transshipment under consistent flow constraints. We consider demand uncertainty represented by a finite set of scenarios and characterize a subset of arcs as so-called fixed arcs. In each scenario, we require an integral flow that satisfies the respective flow balance constraints. In addition, on each fixed arc, we require equal flow for all scenarios. The objective
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A tabu search with geometry-based sparsification methods for angular traveling salesman problems Networks (IF 2.1) Pub Date : 2023-08-16 Rossana Cavagnini, Michael Schneider, Alina Theiß
The angular-metric traveling salesman problem (AngleTSP) aims to find a tour visiting a given set of vertices in the Euclidean plane exactly once while minimizing the cost given by the sum of all turning angles. If the cost is obtained by combining the sum of all turning angles and the traveled distance, the problem is called angular-distance-metric traveling salesman problem (AngleDistanceTSP). In
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A granular iterated local search for the asymmetric single truck and trailer routing problem with satellite depots at DHL Group Networks (IF 2.1) Pub Date : 2023-08-16 Rossana Cavagnini, Michael Schneider, Alina Theiß
To plan the postal deliveries of our industry partner DHL Group (DHL), the single truck and trailer routing problem with satellite depots (STTRPSD) is solved to optimize mail carriers routes. In this application context, instances feature a high number of customers and satellites, and they are based on real street networks. This motivates the study of the asymmetric STTRPSD (ASTTRPSD). The heuristic
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The cumulative school bus routing problem: Polynomial-size formulations Networks (IF 2.1) Pub Date : 2023-08-10 Farnaz Farzadnia, Tolga Bektaş, Jens Lysgaard
This article introduces the cumulative school bus routing problem, which concerns the transport of students from a school using a fleet of identical buses. The objective of the problem is to select a drop-off point for each student among potential locations within a certain walking distance and to generate routes such that the sum of arrival times of all students from their school to their homes is
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Connected graph partitioning with aggregated and non-aggregated gap objective functions Networks (IF 2.1) Pub Date : 2023-08-10 Elena Fernández, Isabella Lari, Justo Puerto, Federica Ricca, Andrea Scozzari
This article deals with the problem of partitioning a graph into p $$ p $$ connected components by optimizing some balancing objective functions related to the vertex weights. Objective functions based on the gap or range of the partition's components, that is, the difference between the maximum and minimum weight of a vertex in the component, have been already introduced in the literature. Here we
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Distance-layer structure of the De Bruijn and Kautz digraphs: Analysis and application to deflection routing Networks (IF 2.1) Pub Date : 2023-07-29 J. Fàbrega, J. Martí-Farré, X. Muñoz
In this article, we present a detailed study of the reach distance-layer structure of the De Bruijn and Kautz digraphs, and we apply our analysis to the performance evaluation of deflection routing in De Bruijn and Kautz networks. Concerning the distance-layer structure, we provide explicit polynomial expressions, in terms of the degree of the digraph, for the cardinalities of some relevant sets of
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Mobile parcel lockers with individual customer service Networks (IF 2.1) Pub Date : 2023-07-28 Rico Kötschau, Ninja Soeffker, Jan Fabian Ehmke
The ongoing growth of e-commerce deliveries has led to a significant increase in last-mile delivery volumes. New technologies are being investigated to provide these deliveries efficiently and in a customer-friendly manner. A common practice is to use fixed parcel lockers (FPLs) to make deliveries independent from the presence of the customer as is the case in attended home deliveries (AHDs). FPLs
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The single robot line coverage problem: Theory, algorithms, and experiments Networks (IF 2.1) Pub Date : 2023-07-25 Saurav Agarwal, Srinivas Akella
Line coverage is the task of servicing a given set of one-dimensional features in an environment. It is important for the inspection of linear infrastructure such as road networks, power lines, and oil and gas pipelines. This paper addresses the single robot line coverage problem for aerial and ground robots by modeling it as an optimization problem on a graph. The problem belongs to the broad class
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Preprocessing for segment routing optimization Networks (IF 2.1) Pub Date : 2023-07-25 Hugo Callebaut, Jérôme De Boeck, Bernard Fortz
In this article we introduce a preprocessing technique to solve the Segment Routing Traffic Engineering Problem optimally using significantly fewer computational resources than previously introduced methods. Segment routing is a recently developed interior gateway routing protocol to be used on top of existing protocols that introduces more flexibility in traffic engineering. In practice, segment routing
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The multi-purpose K-drones general routing problem Networks (IF 2.1) Pub Date : 2023-07-22 James Campbell, Ángel Corberán, Isaac Plana, José M. Sanchis, Paula Segura
In this article, we present and solve the multi-purpose K $$ K $$ -drones general routing problem (MP K $$ K $$ -DGRP). In this optimization problem, a fleet of multi-purpose drones, aerial vehicles that can both make deliveries and conduct sensing activities (e.g., imaging), have to jointly visit a set of nodes to make deliveries and map one or more continuous areas. This problem is motivated by global
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Two-stage stochastic one-to-many driver matching for ridesharing Networks (IF 2.1) Pub Date : 2023-07-14 Gabriel Homsi, Bernard Gendron, Sanjay Dominik Jena
We introduce a modeling framework for stochastic rider-driver matching in many-to-one ridesharing systems, in which drivers have to be selected before the exact rider demand is known. The modeling framework allows for the use of driver booking fees and penalties for unmatched drivers, therefore supporting different system operating modes. We model this problem as a two-stage stochastic set packing
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The inventory routing problem with split deliveries Networks (IF 2.1) Pub Date : 2023-07-12 Nho Minh Dinh, Claudia Archetti, Luca Bertazzi
We study the benefit of introducing split deliveries in the inventory routing problem (IRP), both when the order-up-to level (OU) and the maximum level replenishment policies are applied. We first propose a mathematical formulation and solve it by implementing a branch-and-cut algorithm. Then, we carry out a worst-case analysis to show the cost increase we have in the worst case by using unsplit deliveries
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Targeted multiobjective Dijkstra algorithm Networks (IF 2.1) Pub Date : 2023-07-08 Pedro Maristany de las Casas, Luitgard Kraus, Antonio Sedeño-Noda, Ralf Borndörfer
We introduce the Targeted Multiobjective Dijkstra Algorithm (T-MDA), a label setting algorithm for the One-to-One Multiobjective Shortest Path (MOSP) Problem. It is based on the recently published Multiobjective Dijkstra Algorithm (MDA) and equips it with A*-like techniques. For any explored subpath, a label setting MOSP algorithm decides whether the subpath can be discarded or must be stored as part
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A new MILP formulation for the flying sidekick traveling salesman problem Networks (IF 2.1) Pub Date : 2023-07-05 Maurizio Boccia, Andrea Mancuso, Adriano Masone, Claudio Sterle
Nowadays, truck-and-drone problems represent one of the most studied classes of vehicle routing problems. The Flying Sidekick Traveling Salesman Problem (FS-TSP) is the first optimization problem defined in this class. Since its definition, several variants have been proposed differing for the side constraints related to the operating conditions and for the structure of the hybrid truck-and-drone delivery
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Efficient presolving methods for the influence maximization problem Networks (IF 2.1) Pub Date : 2023-07-04 Sheng-Jie Chen, Wei-Kun Chen, Yu-Hong Dai, Jian-Hua Yuan, Hou-Shan Zhang
We consider the influence maximization problem (IMP) which asks for identifying a limited number of key individuals to spread influence in a network such that the expected number of influenced individuals is maximized. The stochastic maximal covering location problem (SMCLP) formulation is a mixed integer programming formulation that effectively approximates the IMP by the Monte-Carlo sampling. For
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Reliability polynomials of consecutive-k-out-of-n:F systems have unbounded roots Networks (IF 2.1) Pub Date : 2023-06-22 Marilena Jianu, Leonard Dăuş, Vlad-Florin Drăgoi, Valeriu Beiu
This article studies the roots of the reliability polynomials of linear consecutive-k-out-of-n:F systems. We prove that these roots are unbounded in the complex plane, for any fixed k ≥ 2 $$ k\ge 2 $$ . In the particular case k = 2 $$ k=2 $$ , we show that the reliability polynomials have only real roots and highlight the closure of these roots by establishing their explicit formulas. We also point
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Hybrid genetic algorithm for undirected traveling salesman problems with profits Networks (IF 2.1) Pub Date : 2023-06-21 Pengfei He, Jin-Kao Hao, Qinghua Wu
The orienteering problem (OP) and prize-collecting traveling salesman problem (PCTSP) are two typical TSPs with profits, in which each vertex has a profit and the goal is to visit several vertices to optimize the collected profit and travel costs. The OP aims to collect the maximum profit without exceeding the given travel cost. The PCTSP seeks to minimize the travel costs while ensuring a minimum
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On the split reliability of graphs Networks (IF 2.1) Pub Date : 2023-06-20 Jason I. Brown, Isaac McMullin
A common model of robustness of a graph against random failures has all vertices operational, but the edges independently operational with probability p $$ p $$ . One can ask for the probability that all vertices can communicate (all-terminal reliability) or that two specific vertices (or terminals) can communicate with each other (two-terminal reliability). A relatively new measure is split reliability
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A survey on exact algorithms for the maximum flow and minimum-cost flow problems Networks (IF 2.1) Pub Date : 2023-06-20 Oliverio Cruz-Mejía, Adam N. Letchford
Network flow problems form an important and much-studied family of combinatorial optimization problems, with a huge array of practical applications. Two network flow problems in particular have received a great deal of attention: the maximum flow and minimum-cost flow problems. We review the progress that has been made on exact solution algorithms for these two problems, with an emphasis on worst-case
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Achieving feasibility for clustered traveling salesman problems using PQ-trees Networks (IF 2.1) Pub Date : 2023-06-15 Nili Guttmann-Beck, Hadas Meshita-Sayag, Michal Stern
Let H = ⟨ V , 𝒮 ⟩ be a hypergraph, where V $$ V $$ is a set of vertices and 𝒮 is a set of clusters S 1 , … , S m $$ {S}_1,\dots, {S}_m $$ , S i ⊆ V $$ {S}_i\subseteq V $$ , such that the clusters in 𝒮 are not necessarily disjoint. This article considers the feasibility clustered traveling salesman problem, denoted by FCTSP $$ FCTSP $$ . In the FCTSP $$ FCTSP $$ we aim to decide whether a simple
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Exact solution approaches for the discrete α-neighbor p-center problem Networks (IF 2.1) Pub Date : 2023-06-13 Elisabeth Gaar, Markus Sinnl
The discrete α $$ \alpha $$ -neighbor p $$ p $$ -center problem (d- α $$ \alpha $$ - p $$ p $$ CP) is an emerging variant of the classical p $$ p $$ -center problem which recently got attention in literature. In this problem, we are given a discrete set of points and we need to locate p $$ p $$ facilities on these points in such a way that the maximum distance between each point where no facility is
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Node based compact formulations for the Hamiltonian p-median problem Networks (IF 2.1) Pub Date : 2023-06-09 Michele Barbato, Francisco Canas, Luís Gouveia, Pierre Pesneau
In this paper, we introduce, study and analyze several classes of compact formulations for the symmetric Hamiltonian p $$ p $$ -median problem (H p $$ p $$ MP). Given a positive integer p $$ p $$ and a weighted complete undirected graph G = ( V , E ) $$ G=\left(V,E\right) $$ with weights on the edges, the H p $$ p $$ MP on G $$ G $$ is to find a minimum weight set of p $$ p $$ elementary cycles partitioning
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Solving the time capacitated arc routing problem under fuzzy and stochastic travel and service times Networks (IF 2.1) Pub Date : 2023-05-22 Xabier A. Martin, Javier Panadero, David Peidro, Elena Perez-Bernabeu, Angel A. Juan
Stochastic, as well as fuzzy uncertainty, can be found in most real-world systems. Considering both types of uncertainties simultaneously makes optimization problems incredibly challenging. In this paper we propose a fuzzy simheuristic to solve the Time Capacitated Arc Routing Problem (TCARP) when the nature of the travel time can either be deterministic, stochastic or fuzzy. The main goal is to find
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Risk-averse optimization and resilient network flows Networks (IF 2.1) Pub Date : 2023-05-13 Masoud Eshghali, Pavlo A. Krokhmal
We propose an approach to constructing metrics of network resilience, where resilience is understood as the network's amenability to restoring its optimal or near-optimal operations subsequent to unforeseen (stochastic) disruptions of its topology or operational parameters, and illustrated it on the examples of the resilient maximum network flow problem and the resilient minimum cost network problem
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Existence of optimally-greatest digraphs for strongly connected node reliability Networks (IF 2.1) Pub Date : 2023-05-06 Kyle MacKeigan, Danielle Cox, Emily Wright
In this paper, we introduce a new model to study network reliability with node failures. This model, strongly connected node reliability, is the directed variant of node reliability and measures the probability that the operational vertices induce a subdigraph that is strongly connected. If we are restricted to directed graphs with n $$ n $$ vertices and n + 1 ≤ m ≤ 2 n − 3 $$ n+1\le m\le 2n-3 $$ or