Solving the Uncapacitated Single Allocation p-Hub Median Problem on GPU

A parallel genetic algorithm (GA) implemented on GPU clusters is proposed to solve the Uncapacitated Single Allocation p-Hub Median problem. The GA uses binary and integer encoding and genetic operators adapted to this problem. Our GA is improved by generated initial solution with hubs located at middle nodes. The obtained experimental results are compared with the best known solutions on all benchmarks on instances up to 1000 nodes. Furthermore, we solve our own randomly generated instances up to 6000 nodes. Our approach outperforms most well-known heuristics in terms of solution quality and time execution and it allows hitherto unsolved problems to be solved

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

Air Taxi Skyport Location Problem for Airport Access

Witnessing the rapid progress and accelerated commercialization made in recent years for the introduction of air taxi services in near future across metropolitan cities, our research focuses on one of the most important consideration for such services, i.e., infrastructure planning (also known as skyports). We consider design of skyport locations for air taxis accessing airports, where we present the skyport location problem as a modified single-allocation p-hub median location problem integrating choice-constrained user mode choice behavior into the decision process. Our approach focuses on two alternative objectives i.e., maximizing air taxi ridership and maximizing air taxi revenue. The proposed models in the study incorporate trade-offs between trip length and trip cost based on mode choice behavior of travelers to determine optimal choices of skyports in an urban city. We examine the sensitivity of skyport locations based on two objectives, three air taxi pricing strategies, and varying transfer times at skyports. A case study of New York City is conducted considering a network of 149 taxi zones and 3 airports with over 20 million for-hire-vehicles trip data to the airports to discuss insights around the choice of skyport locations in the city, and demand allocation to different skyports under various parameter settings. Results suggest that a minimum of 9 skyports located between Manhattan, Queens and Brooklyn can adequately accommodate the airport access travel needs and are sufficiently stable against transfer time increases. Findings from this study can help air taxi providers strategize infrastructure design options and investment decisions based on skyport location choices.Comment: 25 page

Algoritmos de aproximação para problemas de localização e alocação de terminais

Orientador: Lehilton Lelis Chaves PedrosaDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: No Problema de Localização e Alocação de Terminais, a entrada é um espaço métrico composto por clientes, localidades e um conjunto de pares de clientes; uma solução é um subconjunto das localidades, onde serão abertos terminais, e uma atribuição de cada par de clientes a uma rota, que começa no primeiro cliente, passando em um ou dois terminais, e terminando no segundo cliente. O objetivo é encontrar uma solução que minimize o tamanho de todas as rotas somado com o custo de abertura de terminais. Os algoritmos de aproximação da literatura consideram apenas o caso em que o conjunto de terminais abertos é dado como parte da entrada, e o problema se torna atribuir clientes aos terminais; ou então quando o espaço é definido em classes especiais de grafos. Neste trabalho, apresentamos o primeiro algoritmo de aproximação com fator constante para o problema de, simultaneamente, escolher localidades para abrir terminais e atribuir clientes a estes. A primeira parte desta dissertação cria algoritmos de aproximação para diversas variantes do problema. A estratégia principal é reduzir os problemas de localização e alocação de terminais aos problemas clássicos de localidades, como o problema de localização de instalações e o problema das k-medianas. A redução transforma uma instância de localização e alocação de terminais em uma instância de um destes problemas, que então é resolvida usando algoritmos de aproximação já existentes na literatura. A saída do algoritmo induz uma solução para o problema original, com uma perda constante no fator de aproximação. Na segunda parte, o foco é o Problema de Localização e Alocação Única de Terminais (SAHLP), que é uma variação em que cada cliente deve estar conectado a apenas um terminal, além de não haver limite na quantidade de terminais abertos. A principal contribuição é um algoritmo 2.48-aproximado para o SAHLP, baseado em arredondamento de uma nova formulação de programa linear para o problema. O algoritmo é composto por duas fases: na primeira, a solução fracionária é escalada e um subconjunto de terminais é aberto, e na segunda, atribuímos clientes aos terminais abertos. A primeira fase segue o formato padrão de filtering para problemas de localidades. A segunda, no entanto, exigiu o desenvolvimento de novas ideias e é baseada em múltiplos critérios para realizar a atribuição. A principal técnica atribui cada cliente ao terminal aberto mais próximo, se este estiver em sua vizinhança; caso contrário, o cliente se conecta ao terminal que melhor balanceia múltiplos custos, relacionados à distância entre elesAbstract: In the Hub Location Problem (HLP), the input is a metric space composed of clients, locations and a set of pairs of clients; a solution is a subset of locations to open hubs and an assignment for each pair of clients to a route starting in the first client, passing through one or two hubs and ending in the second client. The objective is to find a solution that minimizes the length of all routes plus the cost of opening hubs. The currently known approximation algorithms consider only the case in which the set of hubs is given as part of the input and the problem is assigning clients to hubs; or when the space is defined on special classes of graphs. In this work, we present the first constant-factor approximation algorithms for the problem of, simultaneously, selecting hubs and allocating clients. The first part of the thesis derives approximation algorithms for several variants of the problem. The main strategy is to reduce the hub location problems to classical location problems, such as Facility Location and k-Median. The reduction transforms an instance of hub location into an instance of a corresponding location problem, which is then solved by known approximation algorithm. The algorithm¿s output induces a solution of the original problem within a constant loss in the approximation ratio. In the second part, we focus on the Single Allocation Hub Location Problem (SAHLP), that is the variant in which a client must be connected to only one hub and there is no limit on the number of open hubs. Our main contribution is a 2.48-approximation algorithm for the SAHLP, based on the rounding of a new linear programming formulation. The algorithm is composed of two phases: in the first one, we scale the fractional solution and open a subset of hub locations, and in the second one, we assign clients to open hubs. The first phase follows the standard filtering framework for location problems. The latter, however, demanded the development of new ideas and is based on a multiple criteria assignment. The main technique is assigning a client to a closest open hub only if there are near open hubs, and otherwise selecting the hub which balances multiple costsMestradoCiência da ComputaçãoMestre em Ciência da Computação2016/12006-1CAPESFAPES

A new formulation and branch-and-cut method for single-allocation hub location problems

A new compact formulation for uncapacitated single-allocation hub location problems with fewer variables than the previous Integer Linear Programming formulations in the literature is introduced. Our formulation works even with costs not based on distances and not satisfying triangle inequality. Moreover, costs can be given in aggregated or disaggregated way. Different families of valid inequalities that strengthen the formulation are developed and a branch-and-cut algorithm based on a relaxed version of the formulation is designed, whose restrictions are inserted in a cut generation procedure together with two sets of valid inequalities. The performance of the proposed methodology is tested on well-known hub location data sets and compared to the most recent and efficient exact algorithms for single-allocation hub location problems. Extensive computational results prove the efficiency of our methodology, that solves large-scale instances in very competitive times

Optimisation of connections to a fibre network

Stronger competition together with the development of new technologies have forced the Telecom Service Providers (TSP's) in the Netherlands to look for sophisticated optimisation methods to reduce the costs of their communication services especially for new areas such as the application of fibre technology.Fibre is being considered as the transmission medium of the future because fibre deadens the signals much less than the traditional media such as copper and coax, a lot of data can be transmitted at the same time and there are only a few failures. Another advantage is that fibre cables are thin and light so that they can be put into the ground rather easily.This article describes optimisation models with the objective to minimise the costs of constructing and managing a fibre network.The optimisation models have been developed to support decisions about the design and use of a fibre network and are based on the practical situation at Enertel being one of the new TSP’s. For Enertel a national backbone was already realised. The main problem to be solved concerned the optimisation of the access to the fibre network.

p-facility Huff location problem on networks

The p-facility Huff location problem aims at locating facilities on a competitive environment so as to maximize the market share. While it has been deeply studied in the field of continuous location, in this paper we study the p-facility Huff location problem on networks formulated as a Mixed Integer Nonlinear Programming problem that can be solved by a branch-and-bound algorithm. We propose two approaches for the initialization and division of subproblems, the first one based on the straightforward idea of enumerating every possible combination of p edges of the network as possible locations, and the second one defining sophisticated data structures that exploit the structure of the combinatorial and continuous part of the problem. Bounding rules are designed using DC (difference of convex) and Interval Analysis tools. In our computational study we compare the two approaches on a battery of 21 networks and show that both of them can handle problems for p ≤ 4 in reasonable computing time.Ministerio de Economía y CompetitividadJunta de AndalucíaHungarian National Research, Development and Innovation OfficeInformation and Communication Technologies COS

Feedback algorithm for switch location : analysis of complexity and application to network design

An accelerated feedback algorithm to solve the single-facility minisum problem is studied with application to designing networks with the star topology. The algorithm, in which the acceleration with respect to the Weiszfeld procedure is achieved by multiplying the current Weiszfeld iterate by an accelerating feedback factor, is shown to converge faster than the accelerating procedures available in the literature. Singularities encountered in the algorithm are discussed in detail. A simple practical exception handling subroutine is developed. Several applications of the algorithm to designing computer networks with the star topology are demonstrated. Applications of the algorithm as a subroutine for multi-switch location problems are considered. Various engineering aspects involved in acquiring and processing coordinates for geographic locations are discussed. A complete algorithm in pseudocode along with the source code listing in Mathematica 4.1 is presented

Hub location and Hub network design

Ankara : The Department of Industrial Engineering and the Institute of Engineering and Science of Bilkent University, 2009.Thesis (Ph.D.) -- Bilkent University, 2009.Includes bibliographical references leaves 138-150.he hub location problem deals with finding the location of hub facilities and allocating the demand nodes to these hub facilities so as to effectively route the demand between origin–destination pairs. Hub location problems arise in various application settings in telecommunication and transportation. In the extensive literature on the hub location problem, it has widely been assumed that the subgraph induced by the hub nodes is complete. Throughout this thesis we relax the complete hub network assumption in hub location problems and focus on designing hub networks that are not necessarily complete. We approach to hub location problems from a network design perspective. In addition to the location and allocation decisions, we also study the decision on how the hub network must be designed. We focus on the single allocation version of the problems where each demand center is allocated to a single hub node. We start with introducing the 3-stop hub covering network design problem. In this problem, we aim to design hub networks so that all origin– destination pairs receive service by visiting at most three hubs on a route. Then, we include hub network design decisions in the classical hub location problems introduced in the literature. We introduce the single allocation incomplete p-hub median, hub location with fixed costs, hub covering, and p-hub center network design problems to the literature. Lastly, we introduce the multimodal hub location and hub network design problem. We include the possibility of using different hub links, and allow for different transportation modes between hubs, and for different types of service time promises between origin–destination pairs, while designing the hub network in the multimodal problem. In this problem, we jointly consider transportation costs and travel times, which are studied separately in hub location problems presented in the literature. Computational analyses with all of the proposed models are presented on the various instances of the CAB data set and on the Turkish network.Alumur, Sibel AlevPh.D