Dynamic programming driven memetic search for the Steiner tree problem with revenues, budget and hop constraints

We present a highly effective dynamic programming driven memetic algorithm for the Steiner tree problem with revenues, budget, and hop constraints (STPRBH), which aims at determining a subtree of an undirected graph, so as to maximize the collected revenue, subject to both budget and hop constraints. The main features of the proposed algorithm include a probabilistic constructive procedure to generate initial solutions, a neighborhood search procedure using dynamic programming to significantly speed up neighborhood exploration, a backbone-based crossover operator to generate offspring solutions, as well as a quality-and-distance updating strategy to manage the population. Computational results based on four groups of 384 well-known benchmarks demonstrate the value of the proposed algorithm, compared to the state of the art approaches. In particular, for the 56 most challenging instances with unknown optima, our algorithm succeeds in providing 45 improved best known solutions within a short computing time. We additionally provide results for a group of 30 challenging instances that are introduced in the paper. We provide a complexity analysis of the proposed algorithm and study the impact of some ingredients on the performance of the algorithm

Algoritmos evolutivos para alguns problemas em telecomunicações

Orientadores: Flavio Keidi Miyazawa, Mauricio Guilherme de Carvalho ResendeTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Nos últimos anos, as redes de telecomunicação tem experienciado um grande aumento no fluxo de dados. Desde a utilização massiva de vídeo sob demanda até o incontável número de dispositivos móveis trocando texto e vídeo, o tráfego alcançou uma escala capaz de superar a capacidade das redes atuais. Portanto, as companhias de telecomunicação ao redor do mundo tem sido forçadas a aumentar a capacidade de suas redes para servir esta crescente demanda. Como o custo de instalar uma infraestrutura de rede é geralmente muito grande, o projeto de redes usa fortemente ferramentas de otimização para manter os custos tão baixos quanto possível. Nesta tese, nós analisamos vários aspectos do projeto e implementação de redes de telecomunicação. Primeiramente, nós apresentamos um novo problema de projeto de redes usado para servir demandas sem fio de dispositivos móveis e rotear tal tráfego para a rede principal. Tais redes de acesso são baseadas em tecnologias sem fio modernos como Wi-Fi, LTE e HSPA. Este problema consideramos várias restrições reais e é difícil de ser resolvido. Nós estudamos casos reais nas vizinhanças de uma grande cidade nos Estados Unidos. Em seguida, nós apresentamos uma variação do problema de localização de hubs usado para modelar as redes principais (backbones ou laços centrais). Este problema também pode ser utilizado para modelar redes de transporte de cargas e passageiros. Nós também estudamos o problema de clusterização correlacionada com sobreposições usado para modelar o comportamento dos usuários quando utilizam seus equipamentos móveis. Neste problema, nós podemos rotular um objeto usando múltiplos rótulos e analisar a conexão entre eles. Este problema é adequado para análise de mobilidade de equipamentos que pode ser usada para estimar o tráfego em uma dada região. E finalmente, nós analisamos o licenciamento de espectro sobre uma perspectiva governamental. Nestes casos, uma agência do governo deseja vender licenças para companhias de telecomunicação para que operem em uma dada faixa de espectro. Este processo usualmente é conduzido usando leilões combinatoriais. Para todos problemas, nós propomos algoritmos genéticos de chaves aleatórias viciadas e modelos de programação linear inteira mista para resolvê-los (exceto para o problema de clusterização correlacionada com sobreposição, devido sua natureza não-linear). Os algoritmos que propusemos foram capazes de superar algoritmos do estado da arte para todos problemasAbstract: Cutting and packing problems are common problems that occur in many industry and business process. Their optimized resolution leads to great profits in several sectors. A common problem, that occur in textil and paper industries, is to cut a strip of some material to obtain several small items, using the minimum length of material. This problem, known by Two Dimensional Strip Packing Problem (2SP), is a hard combinatorial optimization problem. In this work, we present an exact algorithm to 2SP, restricted to two staged cuts (known by Two Dimensional Level Strip Packing, 2LSP). The algorithm uses the branch-and-price technique, and heuristics based on approximation algorithms to obtain upper bounds. The algorithm obtained optimal or almost optimal for small and moderate sized instancesAbstract: In last twenty years, telecommunication networks have experienced a huge increase in data utilization. From massive on-demand video to uncountable mobile devices exchanging text and video, traffic reached scales that overcame the network capacities. Therefore, telecommunication companies around the world have been forced to increase their capacity to serve this increasing demand. As the cost to deploy network infrastructure is usually very large, the design of a network heavily uses optimization tools to keep costs as low as possible. In this thesis, we analyze several aspects of the design and deployment of communication networks. First, we present a new network design problem used to serve wireless demands from mobile devices and route the traffic to the core network. Such access networks are based on modern wireless access technologies such as Wi-Fi, LTE, and HSPA. This problem has several real world constraints and it is hard to solve. We study real cases of the vicinity of a large city in the United States. Following, we present a variation of the hub-location problem used to model these core networks. Such problem is also suitable to model transportation networks. We also study the overlapping correlation clustering problem used to model the user's behavior when using their mobile devices. In such problem, one can label an object with multiple labels and analyzes the connections between them. Although this problem is very generic, it is suitable to analyze device mobility which can be used to estimate traffic in geographical regions. Finally, we analyze spectrum licensing from a governmental perspective. In these cases, a governmental agency wants to sell rights for telecommunication companies to operate over a given spectrum range. This process usually is conducted using combinatorial auctions. For all problems we propose biased random-key genetic algorithms and mixed integer linear programming models (except in the case of the overlapping correlation clustering problem due its non-linear nature). Our algorithms were able to overcome the state of the art algorithms for all problemsDoutoradoCiência da ComputaçãoDoutor em Ciência da Computaçã

Operations Research in action

Wie der Titel bereits andeutet bezieht sich diese Dissertation auf ein Operations Research Projekt, dass der Ä Osterreichische Telekommunikationsanbieter Telekom Austria in den Jahren 2006 bis 2009 durchfÄuhrte. Die wachsende Zahl von Internet Nutzern, neue Anwendungen im Internet und die zunehmende Konkurrenz von mobilem Internet zwingen Festnetzbetreiber wie Telekom Austria ihre Produkte fÄur den Internet Zugang mit hÄoheren Bandbreiten zu versehen. ZwangslÄau¯g mÄussen die Zugangsnetze verbessert werden, was nur mit hohen Investitionskosten erreichbar ist. Aus diesem Grund kommt der kostenoptimalen Planung solcher Netzwerke eine zentrale Rolle zu. Ein wesentliches Projektziel war es, den Planungsprozess mit Methoden der diskreten Optimie- rung aus dem Bereich Network Design zu unterstÄutzen. Die Ergebnisse, die in dieser Disserta- tion beschrieben werden, beschÄaftigen sich mit Algorithmen aus dem Gebiet Facility Location (Bestimmung von Versorgungsstandorten). Vor der PrÄasentation der dazugehÄorigen Theorie und ihrer Anwendung auf die gestellten Problem werden zweitere grÄundlich analysiert. ZunÄachst wird der Telekommunikationsmarkt bis 2009 mit speziellem Fokus auf den Zeitraum zwischen 2006 und 2009 beschrieben. Die Telekommunikationsindustrie hatte bereits einige Strategien zur Verbesserung der Netzwerkinfrastruktur entwickelt. Ihre Relevanz fÄur die ge- stellten Probleme wird herausgearbeitet Dem folgt eine Au°istung der Problemspezi¯kationen, wie sie in der Evaluierungsphase des Projekts mit den beteiligten Anwendern erstellt wurde. Mit Hilfe eines dynamischen Programmes wird die gestellte Fragestellung unter BerÄucksichtigung aller Spezi¯kationen gelÄost. Eine Au°istung von Bedingungen, wann dieser Algorithmus die optimale LÄosung liefert, und die dazugehÄorigen Beweise beschlie¼en Kapitel 1. In der Folge stellte sich allerdings heraus, dass die Praktiker mit dieser ersten LÄosung nicht zufrieden waren. Die Liste der Spezi¯kationen war nicht vollstÄandig. Sie musste verÄandert und erweitert werden. Mangelnde E±zienz machte die LÄosungen fÄur die Praxis unbrauchbar. Die LÄosungen enthielten Versorgungsstandorte, die minder ausgelastet waren (underutilized), d.h. diesen Standorten waren zu wenige Kunden zugeordnet worden. Solche Lokationen mussten aus den LÄosungen entfernt werden. Dann aber waren die Verbleibenden so zu repositionieren, dass die Versorgung mit einer vorgegebenen MindestÄubertragungsrate fÄur die grÄo¼tmÄogliche Menge an Kunden sichergestellt werden konnte. Diese Strategie wurde mit Hilfe des Konzepts der k-Mediane umgesetzt: Unter der Nebenbedingung, dass die Anzahl der Standorte durch eine Konstante k beschrÄankt ist, wird die optimale Zuordnung von Kunden zu Versorgungs- standorten, d.h. ihre Versorgung, gesucht. Anschlie¼end lÄost man dann k-Median Probleme fÄur verschiedene Werte von k und bestimmt die Mindestauslastungen und Versorgungsraten, die diese LÄosungen erzielen. Dieses Vorgehen versetzt den Anwender in die Lage unter verschie- denen LÄosungen zwischen e±zienter Auslastung der Versorgungsstandorten und der HÄohe der Versorgungsraten balancieren zu kÄonnen. In Kapitel 2 werden zunÄachst die Ereignisse und Diskussionen beschrieben, die eine ÄAnderung der LÄosungsstrategie notwendig machten, und die geÄanderten bzw. neuen Spezi¯kationen wer- den prÄasentiert. Dem folgt die Vorstellung der Theorie der k-Mediane inklusive der Beschrei- bung eines Algorithmus aus der Literatur. Am Ende des zweiten Kapitels wird eine Variante dieses Algorithmus entwickelt, der fÄur die spezi¯schen Anforderungen noch besser geeignet ist: Der Algorithmus aus der Literatur fÄugt Lokationen schrittweise in die LÄosung ein, d.h. pro Iteration erhÄoht sich die Anzahl der Versorgungsstandorte um einen, bis die maximale Anzahl von Lokationen erreicht ist. Im Falle von Zugangsnetzen ist die zu erwartende Anzahl von Standorten aber eher gro¼. Daher ist es vorteilhafter die gewÄunschte Anzahl von oben, durch Reduktion der Anzahl von Versorgungsstandorten in der LÄosung zu erreichen. Kapitel 3 liefert eine extensive empirische Analyse von 106 verschiedenen Zugangsnetzen. Kon- kreter Zweck dieser Demonstration ist es einen Eindruck zu vermittelt, wie man die entwickel- ten und adaptierten Methoden bei der Vorbereitung des Planungsprozesses einsetzen kann. So ist es einerseits mÄoglich strategischen Fragestellungen vorab zu analysieren (z.B. E®ekt der Erzwingung des HV Kreises, Balance zwischen Auslastung der Versorgungsstandorte und der Versorgungsrate), und andererseits VorschlÄage fÄur passende Planungsprozesse fÄur die An- wender zu entwickeln (z.B. durch Laufzeitanalysen). ZusÄatzlich werden die beiden Methoden zur LÄosung des k-Median Problems, die in dieser Abreit vorgestellt werden, noch bzgl. ihres Laufzeitverhaltens verglichen.As indicated by the title this thesis is based on an Operations Research project which was conducted at the Austrian telecommunications provider Telekom Austria between 2006 and 2009. An increasing number of internet users, new internet applications and the growing competition of mobile internet access force ¯xed line providers like Telekom Austria to o®er higher rates for data transmission via their access networks. As a consequence access nets have to be improved which leads to investments of signi¯cant size. Therefore, minimizing such investments by a cost optimal planning of networks becomes a key issue. The main goal of the project was to support the planning process by utilizing discrete opti- mization methods from the ¯eld of network design. The key results which are presented in this thesis are algorithms for facility location. However, before dealing with the theory and the solutions | in practice as well as in this thesis | a thorough analysis of the stated problem is undertaken. To begin with the telecommunication market before 2006 and especially between 2006 and 2009 is reviewed to provide some background information. The industry had already developed di®erent strategies to improve ¯xed line infrastructure. Their relevance for the stated problem is presented. Furthermore, the most important problem speci¯cations as they were gathered in cooperation with the practitioners are listed and discussed in detail. A ¯rst solution was based on a dynamic program for solving the facility location problem which was derived from the speci¯cations. The statement of conditions for the optimality of this algorithm and their proofs conclude Chapter 1. It turned out that this ¯rst solution did not provide the desired result. It rather fostered the discussion process between operations researches and practitioners. New speci¯cations were added to the existing list. The planners dismissed these ¯rst solutions because they were not e±cient enough. These solutions contained facilities which were underutilized, i.e. too few customers were assigned to such facilities. To overcome this problem facilities of low utilization had to be removed from the solutions. The remaining facilities were rearranged in a way to maximize the coverage with a certain minimum transmission rate. This strategy was realized by adapting the concept of the k-median problem: The number of facilities is bounded whereas simultaneously the number of optimally supplied customers is maximized. Then for di®erent bounds the minimum facility utilization is reported. That way the practitioner is enabled to ¯nd the optimal balance between e±cient facility utilization and coverage of customer demands. After sketching the events and discussions which made further development necessary and listing the additional speci¯cations, the theory of the k-median problem is presented and a basic algorithm from the literature is cited. For the speci¯c requirements of the given problem a variant of the algorithm is developed and described at the end of Chapter 2: The algorithm from the literature inserts facilities one by one into the solution that way approaching the bound in an ascending manner. However, since the expected number of facilities is usually large it is more advantageous to approach the bound from above in a descending manner. Finally, an extensive empirical study of 106 di®erent local access areas is presented. The main purpose of this demonstration is to give a concrete impression of how the adapted and developed methods can be utilized in preparation of the planning process by studying strategic questions (e.g. CO circle enforcement, balancing between facility utilization and coverage) and by providing information (runtime) which is useful to set up an appropriate working environment for the future users. Additionally, the two variants of the k-median algorithm | the ascending and the descending method | can be compared

Fuelling the zero-emissions road freight of the future: routing of mobile fuellers

The future of zero-emissions road freight is closely tied to the sufficient availability of new and clean fuel options such as electricity and Hydrogen. In goods distribution using Electric Commercial Vehicles (ECVs) and Hydrogen Fuel Cell Vehicles (HFCVs) a major challenge in the transition period would pertain to their limited autonomy and scarce and unevenly distributed refuelling stations. One viable solution to facilitate and speed up the adoption of ECVs/HFCVs by logistics, however, is to get the fuel to the point where it is needed (instead of diverting the route of delivery vehicles to refuelling stations) using "Mobile Fuellers (MFs)". These are mobile battery swapping/recharging vans or mobile Hydrogen fuellers that can travel to a running ECV/HFCV to provide the fuel they require to complete their delivery routes at a rendezvous time and space. In this presentation, new vehicle routing models will be presented for a third party company that provides MF services. In the proposed problem variant, the MF provider company receives routing plans of multiple customer companies and has to design routes for a fleet of capacitated MFs that have to synchronise their routes with the running vehicles to deliver the required amount of fuel on-the-fly. This presentation will discuss and compare several mathematical models based on different business models and collaborative logistics scenarios

Computer science: the hardware software and heart of IT

1st edition, 201