Using genetic algorithms for the single allocation hub location problem

Hub location problem is an NP-hard problem that frequently arises in the design of transportation and distribution systems, postal delivery networks, and airline passenger flow. This work focuses on the Single Allocation Hub Location Problem (SAHLP). Genetic Algorithms (GAs) for the capacitated and uncapacitated variants of the SAHLP based on new chromosome representations and crossover operators are explored. The GAs is tested on two well-known sets of real-world problems with up to 200 nodes. The obtained results are very promising. For most of the test problems the GA obtains improved or best-known solutions and the computational time remains low. The proposed GAs can easily be extended to other variants of location problems arising in network design planning in transportation systems.

Multi-Objective Genetic Algorithms for the Single Allocation Hub Location Problem

Hub Location Problems play vital economic roles in transportation and telecommunication networks where goods or people must be efficiently transferred from an origin to a destination point whilst direct origin-destination links are impractical. This work investigates the single allocation hub location problem, and proposes a genetic algorithm (GA) approach for it. The effectiveness of using a single-objective criterion measure for the problem is first explored. Next, a multi-objective GA employing various fitness evaluation strategies such as Pareto ranking, sum of ranks, and weighted sum strategies is presented. The effectiveness of the multi-objective GA is shown by comparison with an Integer Programming strategy, the only other multi-objective approach found in the literature for this problem. Lastly, two new crossover operators are proposed and an empirical study is done using small to large problem instances of the Civil Aeronautics Board (CAB) and Australian Post (AP) data sets.

Models and algorithms for the capacitated location-routing problem

Le problème de localisation-routage avec capacités (PLRC) apparaît comme un problème clé dans la conception de réseaux de distribution de marchandises. Il généralisele problème de localisation avec capacités (PLC) ainsi que le problème de tournées de véhicules à multiples dépôts (PTVMD), le premier en ajoutant des décisions liées au routage et le deuxième en ajoutant des décisions liées à la localisation des dépôts. Dans cette thèse on dévelope des outils pour résoudre le PLRC à l’aide de la programmation mathématique. Dans le chapitre 3, on introduit trois nouveaux modèles pour le PLRC basés sur des flots de véhicules et des flots de commodités, et on montre comment ceux-ci dominent, en termes de la qualité de la borne inférieure, la formulation originale à deux indices [19]. Des nouvelles inégalités valides ont été dévelopées et ajoutées aux modèles, de même que des inégalités connues. De nouveaux algorithmes de séparation ont aussi été dévelopés qui dans la plupart de cas généralisent ceux trouvés dans la litterature. Les résultats numériques montrent que ces modèles de flot sont en fait utiles pour résoudre des instances de petite à moyenne taille. Dans le chapitre 4, on présente une nouvelle méthode de génération de colonnes basée sur une formulation de partition d’ensemble. Le sous-problème consiste en un problème de plus court chemin avec capacités (PCCC). En particulier, on utilise une relaxation de ce problème dans laquelle il est possible de produire des routes avec des cycles de longueur trois ou plus. Ceci est complété par des nouvelles coupes qui permettent de réduire encore davantage le saut d’intégralité en même temps que de défavoriser l’apparition de cycles dans les routes. Ces résultats suggèrent que cette méthode fournit la meilleure méthode exacte pour le PLRC. Dans le chapitre 5, on introduit une nouvelle méthode heuristique pour le PLRC. Premièrement, on démarre une méthode randomisée de type GRASP pour trouver un premier ensemble de solutions de bonne qualité. Les solutions de cet ensemble sont alors combinées de façon à les améliorer. Finalement, on démarre une méthode de type détruir et réparer basée sur la résolution d’un nouveau modèle de localisation et réaffectation qui généralise le problème de réaffectaction [48].

Confidence in heuristic solutions?

Solutions to combinatorial optimization problems frequently rely on heuristics to minimize an objective function. The optimum is sought iteratively and pre-setting the number of iterations dominates in operations research applications, which implies that the quality of the solution cannot be ascertained. Deterministic bounds offer a mean of ascertaining the quality, but such bounds are available for only a limited number of heuristics and the length of the interval may be difficult to control in an application. A small, almost dormant, branch of the literature suggests using statistical principles to derive statistical bounds for the optimum. We discuss alternative approaches to derive statistical bounds. We also assess their performance by testing them on 40 test p-median problems on facility location, taken from Beasley’s OR-library, for which the optimum is known. We consider three popular heuristics for solving such location problems; simulated annealing, vertex substitution, and Lagrangian relaxation where only the last offers deterministic bounds. Moreover, we illustrate statistical bounds in the location of 71 regional delivery points of the Swedish Post. We find statistical bounds reliable and much more efficient than deterministic bounds provided that the heuristic solutions are sampled close to the optimum. Statistical bounds are also found computationally affordable.

Distance measure and the p-median problem in rural areas

The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region witha sparse, heterogeneous network and a non-symmetric distribution of thepopulation. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (2-100 facilities). We find that the network distance give as gooda solution as the travel-time network. The Euclidean distance gives solutions some 2-7 per cent worse than the network distances, and the solutions deteriorate with increasing P. Our conclusions extend to intra-urban location problems.

Robustness to non-normality of various tests for the one-sample location problem

This paper studies the effect of the normal distribution assumption on the power and size of the sign test, Wilcoxon's signed rank test and the t-test when used in one-sample location problems. Power functions for these tests under various skewness and kurtosis conditions are produced for several sample sizes from simulated data using the g-and-k distribution of MacGillivray and Cannon.

Abordagens complementares para problemas de p-medianas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Integração de modelos de localização a sistemas de informações geográficas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A column generation approach to capacitated p-median problems

The Capacitated p-median problem (CPMP) seeks to solve the optimal location of p facilities, considering distances and capacities for the service to be given by each median. In this paper we present a column generation approach to CPMP. The identified restricted master problem optimizes the covering of 1-median clusters satisfying the capacity constraints, and new columns are generated considering knapsack subproblems. The Lagrangean/surrogate relaxation has been used recently to accelerate subgradient like methods. In this work the Lagrangean/surrogate relaxation is directly identified from the master problem dual and provides new bounds and new productive columns through a modified knapsack subproblem. The overall column generation process is accelerated, even when multiple pricing is observed. Computational tests are presented using instances taken from real data from Sao Jose dos Campos' city.

Um algoritmo de busca tabu para problemas de localização não capacitados

In this work, a tabu search algorithm for solving uncapacitated location problems is presented. The uncapacitated location problem is a classic problem of localization and occurs in many practical situations. The problem consists in determining in a network, at the minimum possible cost, the better localization, in a network, for the installation of facilities in order to attend the customers' associated demands, at the minimum possible cost. One admits that there exists a cost associated with the opening of a facility and a cost of attendance of each customer by any open facilities. In the particular case of the uncapacitated location problem there is no capacity limitation to attend the customers’ demands. There are some parameters in the algorithm that influence the solution’s quality. These parameters were tested and optimal values for them were obtained. The results show that the proposed algorithm is able to find the optimal solution for all small tested problems keeping the compromise between solution’s quality and computational time. However, to solve bigger problems, the structure of the algorithm must be changed in its structure. The implemented algorithm is integrated to a computational platform for solution of logistic problems

A hybrid method for the probabilistic maximal covering location-allocation problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

On arc-routing problems

Das Basisproblem von Arc-Routing Problemen mit mehreren Fahrzeugen ist das Capacitated Arc-Routing Problem (CARP). Praktische Anwendungen des CARP sind z.B. in den Bereichen Müllabfuhr und Briefzustellung zu finden. Das Ziel ist es, einen kostenminimalen Tourenplan zu berechnen, bei dem alle erforderlichen Kanten bedient werden und gleichzeitig die Fahrzeugkapazität eingehalten wird. In der vorliegenden Arbeit wird ein Cut-First Branch-and-Price Second Verfahren entwickelt. In der ersten Phase werden Schnittebenen generiert, die dem Master Problem in der zweiten Phase hinzugefügt werden. Das Subproblem ist ein kürzeste Wege Problem mit Ressourcen und wird gelöst um neue Spalten für das Master Problem zu liefern. Ganzzahlige CARP Lösungen werden durch ein neues hierarchisches Branching-Schema garantiert. Umfassende Rechenstudien zeigen die Effektivität dieses Algorithmus. Kombinierte Standort- und Arc-Routing Probleme ermöglichen eine realistischere Modellierung von Zustellvarianten bei der Briefzustellung. In dieser Arbeit werden jeweils zwei mathematische Modelle für Park and Loop und Park and Loop with Curbline vorgestellt. Die Modelle für das jeweilige Problem unterscheiden sich darin, wie zulässige Transfer Routen modelliert werden. Während der erste Modelltyp Subtour-Eliminationsbedingungen verwendet, werden bei dem zweiten Modelltyp Flussvariablen und Flusserhaltungsbedingungen eingesetzt. Die Rechenstudie zeigt, dass ein MIP-Solver den zweiten Modelltyp oft in kürzerer Rechenzeit lösen kann oder bei Erreichen des Zeitlimits bessere Zielfunktionswerte liefert.

Problemas geométricos de localización

En esta memoria estudiamos problemas geométricos relacionados con la Localización de Servicios. La Localización de Servicios trata de la ubicación de uno o más recursos (radares, almacenes, pozos exploradores de petróleo, etc) de manera tal que se optimicen ciertos objetivos (servir al mayor número de usuarios posibles, minimizar el coste de transporte, evitar la contaminación de poblaciones cercanas, etc). La resolución de este tipo de problemas de la vida real da lugar a problemas geométricos muy interesantes. En el planteamiento geométrico de muchos de estos problemas los usuarios potenciales del servicio son representados por puntos mientras que los servicios están representados por la figura geométrica que mejor se adapta al servicio prestado: un anillo para el caso de radares, antenas de radio y televisión, aspersores, etc, una cuña si el servicio que se quiere prestar es de iluminación, por ejemplo, etc. Estas son precisamente las figuras geométricas con las que hemos trabajado. En nuestro caso el servicio será sólo uno y el planteamiento formal del problema es como sigue: dado un anillo o una cuña de tamaño fijo y un conjunto de n puntos en el plano, hallar cuál tiene que ser la posición del mismo para que se cubra la mayor cantidad de puntos. Para resolver estos problemas hemos utilizado arreglos de curvas en el plano. Los arreglos son una estructura geométrica bien conocida y estudiada dentro de la Geometría Computacional. Nosotros nos hemos centrado en los arreglos de curvas de Jordán no acotadas que se intersectan dos a dos en a lo sumo dos puntos, ya que estos fueron los arreglos con los que hemos tenido que tratar para la resolución de los problemas. De entre las diferentes técnicas para la construcción de arreglos hemos estudiado el método incremental, ya que conduce a algoritmos que son en general más sencillos desde el punto de vista de la codificación. Como resultado de este estudio hemos obtenido nuevas cotas que mejoran la complejidad del tiempo de construcción de estos arreglos con algoritmos incrementales. La nueva cota Ο(n λ3(n)) supone una mejora respecto a la cota conocida hasta el momento: Ο(nλ4(n)).También hemos visto que en ciertas condiciones estos arreglos pueden construirse en tiempo Ο(nλ2(n)), que es la cota óptima para la construcción de estos arreglos. Restringiendo el estudio a curvas específicas, hemos obtenido que los arreglos de n circunferencias de k radios diferentes pueden construirse en tiempo Ο(n2 min(log(k),α(n))), resultado válido también para arreglos de elipses, parábolas o hipérbolas de tamaños diferentes cuando las figuras son todas isotéticas.---ABSTRACT--- In this work some geometric problems related with facility location are studied. Facility location deals with location of one or more facilities (radars, stores, oil wells, etc.) in such way that some objective functions are to be optimized (to cover the maximum number of users, to minimize the cost of transportation, to avoid pollution in the nearby cities, etc.). These kind of real world problems give rise to very interesting geometrical problems. In the geometric version of many of these problems, users are represented as points while facilities are represented as different geometric objects depending on the shape of the corresponding facility: an annulus in the case of radars, radio or TV antennas, agricultural spraying devices, etc. A wedge in many illumination or surveillance applications. These two shapes are the geometric figures considered in this Thesis. The formal setting of the problem is the following: Given an annulus or a wedge of fixed size and a set of n points in the plane, locate the best position for the annulus or the wedge so that it covers as many points as possible. Those problems are solved by using arrangements of curves in the plane. Arrangements are a well known geometric structure. Here one deals with arrangements of unbounded Jordan curves which intersect each other in at most two points. Among the different techniques for computing arrangements, incremental method is used because it is easier for implementations. New time complexity upper bounds has been obtained in this Thesis for the construction of such arrangements by means of incremental algorithms. New upper bound is Ο(nλ3(n)) which improves the best known up to now Ο(nλ4(n)). It is shown also that sometimes this arrangements can be constructed in Ο(nλ2(n)), which is the optimal bound for constructing these arrangements. With respect to specific type of curves, one gives an Ο(n2 min(log(k),α(n))), algorithm that constructs the arrangement of a set of n circles of k different radii. This algorithm is also valid for ellipses parabolas or hyperbolas of k different sizes when all of them are isothetic.

Algorithmic Background of the Host Recommendation in the Adaptive Distributed Multimedia Server

Partial support of the Hungarian State Eötvös Scholarship, the Hungarian National Science Fund (Grant No. OTKA 42559 and 42706) and the Mobile Innovation Center, Hungary is gratefully acknowledged.

Enabling long journeys in electric vehicles:design and demonstration of an infrastructure location model

This research develops a methodology and model formulation which suggests locations for rapid chargers to help assist infrastructure development and enable greater battery electric vehicle (BEV) usage. The model considers the likely travel patterns of BEVs and their subsequent charging demands across a large road network, where no prior candidate site information is required. Using a GIS-based methodology, polygons are constructed which represent the charging demand zones for particular routes across a real-world road network. The use of polygons allows the maximum number of charging combinations to be considered whilst limiting the input intensity needed for the model. Further polygons are added to represent deviation possibilities, meaning that placement of charge points away from the shortest path is possible, given a penalty function. A validation of the model is carried out by assessing the expected demand at current rapid charging locations and comparing to recorded empirical usage data. Results suggest that the developed model provides a good approximation to real world observations, and that for the provision of charging, location matters. The model is also implemented where no prior candidate site information is required. As such, locations are chosen based on the weighted overlay between several different routes where BEV journeys may be expected. In doing so many locations, or types of locations, could be compared against one another and then analysed in relation to siting practicalities, such as cost, land permission and infrastructure availability. Results show that efficient facility location, given numerous siting possibilities across a large road network can be achieved. Slight improvements to the standard greedy adding technique are made by adding combination weightings which aim to reward important long distance routes that require more than one charge to complete.