Star p-hub median problem with modular arc capacities

Cataloged from PDF version of article.We consider the hub location problem, where p hubs are chosen from a given set of nodes, each nonhub node is connected to exactly one hub and each hub is connected to a central hub. Links are installed on the arcs of the resulting network to route the traffic. The aim is to find the hub locations and the connections to minimize the link installation cost.We propose two formulations and a heuristic algorithm to solve this problem. The heuristic is based on Lagrangian relaxation and local search.We present computational results where formulations are compared and the quality of the heuristic solutions are tested. 2007 Elsevier Ltd. All rights reserved

Network hub locations problems: the state of the art

Cataloged from PDF version of article.Hubs are special facilities that serve as switching, transshipment and sorting points in many-to-many distribution systems. The hub location problem is concerned with locating hub facilities and allocating demand nodes to hubs in order to route the traffic between origin-destination pairs. In this paper we classify and survey network hub location models. We also include some recent trends on hub location and provide a synthesis of the literature. (C) 2007 Elsevier B.V. All rights reserved

A Lagrangean Relaxation Approach for the Modular Hub Location Problem

Hub location problems deal with the location of hub facilities and the allocation of the demand nodes to hub facilities so as to effectively route the demand between origin–destination pairs. Transportation systems such as mail, freight, passenger and even telecommunication systems most often employ hub and spoke networks to provide a strong balance between high service quality and low costs resulting in an economically competitive operation. In this study the Modular Hub Location Problem (Multiple assignments without direct connections) (MHLP-MA) is introduced. A Lagrangean relaxation method is used to approximately solve large scale instances. It relaxes a set of complicating constraints to efficiently obtain lower and upper bounds on the optimal solution of the problem. Computational experiments are performed in order to evaluate the effectiveness and limitations of the proposed model and solution method

Grasp and tabu search for redesigning web communities

Web topologies are commonly characterised by hierarchical structures and highly unbalanced compositions, as illustrated by the difference of centrality and connectivity as to their elements. The major interest of the problem addressed in this paper lies in restructuring web communities to reduce these initial disequilibria so as to democratise information access or even for the purpose of preserving contents distributed on the Internet. Discussion of this issue thus leads to a hub location problem, formalised by network and integer programming models. Due to its highly complex nature, a GRASP and a tabu search heuristics were developed to find good quality feasible solutions to the problem. The set of test instances includes web communities obtained by crawling the web and using epistemic boundaries, as well as other randomly generated communities, built with specific network analysis software. The experiment demonstrated that the metaheuristics produced low costs and balanced structures, at least for the lower dimension web communities considered. All the redesigned web communities are more closely connected than before and the average distance among their elements reduced

On hub location problems in geographically flexible networks

The authors were partially supported by research groups SEJ-584 and FQM-331 (Junta de Andalucia) and projects MTM2016-74983-C02-01 (Spanish Ministry of Education and Science/FEDER), FEDER-US-1256951, P18-FR-1422, P18-FR-2369 (Junta de Andalucia), CEI-3FQM331 (Andalucia Tech), and NetmeetData (Fundacion BBVA - Big Data 2019). We also would like to acknowledge Elena Fernandez (Universidad de Cadiz) for her useful and detailed comments on previous versions of this manuscript.In this paper, we propose an extension of the uncapacitated hub location problem where the potential positions of the hubs are not fixed in advance. Instead, they are allowed to belong to a region around an initial discrete set of nodes. We give a general framework in which the collection, transportation, and distribution costs are based on norm-based distances and the hub-activation setup costs depend not only on the location of the hub that are opened but also on the size of the region where they are placed. Two alternative mathematical programming formulations are proposed. The first one is a compact formulation while the second one involves a family of constraints of exponential size that we separate efficiently giving rise to a branch-and-cut algorithm. The results of an extensive computational experience are reported showing the advantages of each of the approaches.Junta de Andalucia SEJ-584 FQM-331 FEDER-US-1256951 P18-FR-1422 P18-FR-2369Spanish Government European Commission MTM2016-74983-C02-01Andalucia Tech CEI-3FQM331NetmeetData (Fundacion BBVA - Big Data 2019

Model and solution methods for some hub location problems

In this thesis we study some hub location problems in the context of transportation networks. These are combinatorial optimization problems appearing in situations where there is a need of transporting some traffic, like items, people, and information, from many origins to many destinations. Instead of sending these flows using a direct shipment between all pairs of nodes in the network, a subset of these nodes is selected to use as hubs, with the aim of consolidating and distribute the flows. Thus, hubs induce a subnetwork that sends the traffic more efficiently and at a cheaper cost, allowing economies of scale when large amounts of traffic between nodes on this subnet are transported. We study different variants of hub location problems that try to model several real world situations and characteristics. In all of them, we aim to minimize the cost of sending traffic through the transportation network.In this thesis we study some hub location problems in the context of transportation networks. These are combinatorial optimization problems appearing in situations where there is a need of transporting some traffic, like items, people, and information, from many origins to many destinations. Instead of sending these flows using a direct shipment between all pairs of nodes in the network, a subset of these nodes is selected to use as hubs, with the aim of consolidating and distribute the flows. Thus, hubs induce a subnetwork that sends the traffic more efficiently and at a cheaper cost, allowing economies of scale when large amounts of traffic between nodes on this subnet are transported. We study different variants of hub location problems that try to model several real world situations and characteristics. In all of them, we aim to minimize the cost of sending traffic through the transportation network

Multi-period maximal covering location problem with capacitated facilities and modules for natural disaster relief services

The paper aims to study a multi-period maximal covering location problem with the configuration of different types of facilities, as an extension of the classical maximal covering location problem (MCLP). The proposed model can have applications such as locating disaster relief facilities, hospitals, and chain supermarkets. The facilities are supposed to be comprised of various units, called the modules. The modules have different sizes and can transfer between facilities during the planning horizon according to demand variation. Both the facilities and modules are capacitated as a real-life fact. To solve the problem, two upper bounds-(LR1) and (LR2)-and Lagrangian decomposition (LD) are developed. Two lower bounds are computed from feasible solutions obtained from (LR1), (LR2), and (LD) and a novel heuristic algorithm. The results demonstrate that the LD method combined with the lower bound obtained from the developed heuristic method (LD-HLB) shows better performance and is preferred to solve both small- and large-scale problems in terms of bound tightness and efficiency especially for solving large-scale problems. The upper bounds and lower bounds generated by the solution procedures can be used as the profit approximation by the managerial executives in their decision-making process

Topological Cluster Analysis Reveals the Systemic Organization of the Caenorhabditis elegans Connectome

The modular organization of networks of individual neurons interwoven through synapses has not been fully explored due to the incredible complexity of the connectivity architecture. Here we use the modularity-based community detection method for directed, weighted networks to examine hierarchically organized modules in the complete wiring diagram (connectome) of Caenorhabditis elegans (C. elegans) and to investigate their topological properties. Incorporating bilateral symmetry of the network as an important cue for proper cluster assignment, we identified anatomical clusters in the C. elegans connectome, including a body-spanning cluster, which correspond to experimentally identified functional circuits. Moreover, the hierarchical organization of the five clusters explains the systemic cooperation (e.g., mechanosensation, chemosensation, and navigation) that occurs among the structurally segregated biological circuits to produce higher-order complex behaviors