Problème de déploiement de ressources dans le cas des feux de forêts majeurs - Opérations aériennes

Chaque année le feu brûle quelques dizaines de milliers d’hectares de forêts québécoises. Le coût annuel de prévention et de lutte contre les feux de forêts au Québec est de l’ordre de plusieurs dizaines de millions de dollars. Le présent travail contribue à la réduction de ces coûts à travers l’automatisation du processus de planification des opérations de suppression des feux de forêts majeurs. Pour ce faire, un modèle mathématique linéaire en nombres entiers a été élaboré, résolu et testé; introduisant un nouveau cas particulier à la littérature des Problèmes de Tournées de Véhicules (VRP). Ce modèle mathématique concerne le déploiement aérien des ressources disponibles pour l’extinction des incendies. Le modèle élaboré a été testé avec CPLEX sur des cas tirés de données réelles. Il a permis de réduire le temps de planification des opérations d’extinction des feux de forêts majeurs de 75% dans les situations courantes.

Otimização da recolha de resíduos urbanos : caso de estudo de Aveiro

O elevado custo da operação de recolha de resíduos urbanos e a necessidade de cumprir metas dispostas em instrumentos legais são duas motivações que conduzem à necessidade de otimizar o serviço da recolha de resíduos. A otimização da recolha de resíduos é um problema de elevada complexidade de resolução que envolve a análise de redes de transporte. O presente trabalho propõe soluções de otimização da recolha de resíduos urbanos indiferenciados, a partir de um caso de estudo: o percurso RSU I 06 do município de Aveiro. Para este efeito, recorreu-se a uma aplicação informática de representação e análise geográfica: software ArcGIS denominada ArcMap e sua extensão Network Analyst, desenvolvida para calcular circuitos otimizados entre pontos de interesse. O trabalho realizado de aplicação do Network Analyst inclui a apresentação de duas das suas funcionalidades (Route e Vehicle Routing Problem). Em relação ao atual circuito de recolha e com base nos ensaios efetuados, foi possível concluir que esta aplicação permite obter circuitos de recolha otimizados mais curtos ou com menor duração. Contudo, ao nível da gestão permitiu concluir que, com a atual capacidade de contentorização, seria viável reduzir a frequência de recolha de seis vezes por semana para metade, dividindo a área de recolha em duas áreas, de acordo com as necessidades de cada local, reduzindo ainda mais o esforço de recolha. A aplicação do Network Analyst ao caso de estudo, permitiu concluir que é um software com muito interesse no processo de gestão da recolha de resíduos urbanos, apesar de apresentar algumas restrições de aplicação e que a qualidade/eficácia do procedimento de otimização depende da qualidade dos dados de entrada, em particular do descritivo geográfico disponível para os arruamentos e, em larga medida, também depende do modelo de gestão considerado.

O problema de alocação de berços: um estudo das heurísticas simulated annealing e algoritmo genético

Este trabalho apresenta um estudo de caso das heurísticas Simulated Annealing e Algoritmo Genético para um problema de grande relevância encontrado no sistema portuário, o Problema de Alocação em Berços. Esse problema aborda a programação e a alocação de navios às áreas de atracação ao longo de um cais. A modelagem utilizada nesta pesquisa é apresentada por Mauri (2008) [28] que trata do problema como uma Problema de Roteamento de Veículos com Múltiplas Garagens e sem Janelas de Tempo. Foi desenvolvido um ambiente apropriado para testes de simulação, onde o cenário de análise foi constituido a partir de situações reais encontradas na programação de navios de um terminal de contêineres. Os testes computacionais realizados mostram a performance das heurísticas em relação a função objetivo e o tempo computacional, a m de avaliar qual das técnicas apresenta melhores resultados.

Uma metodologia heurística para minimizar o roteiro nos serviços de leitura de hidrômetros

Este trabalho tem por objetivo propor uma metodologia heurística para o Problema de Cobertura de Arcos aplicado aos serviços de saneamento, em específico na leitura de hidrômetros. Dentro deste contexto desenvolveu-se um aplicativo que permite o planejamento de rotas de maneira que os custos em distância percorrida sejam reduzidos e mantenham-se aproximadamente os mesmos em todos os percursos. A metodologia foi dividida em etapas. Na primeira etapa, para compreender melhor o problema, fez-se uma pesquisa de campo organizando os dados disponibilizados por uma empresa de saneamento. A segunda etapa foi caracterizada pela determinação de pontos em cada metade de trechos de quadra e nas interseções de ruas, os quais foram cadastrados, em um mapa georeferenciado. Este mapa contemplou a região escolhida para o estudo e os pontos cadastrados serviram para determinar e consequentemente, designar as medianas relacionadas, o que constitui a terceira etapa. Para isso utilizou-se respectivamente o algoritmo de Teitz Bart Modificado por CADP e o algoritmo de designação de Gillet e Johnson adaptado. Ao final desta etapa formaram-se subsetores dentro de um setor específico. Na última etapa encontrou-se as rotas de cada subsetor através do algoritmo genético. O aplicativo desenvolvido permitiu flexibilidade de ações, dando autonomia para o usuário na escolha das opções de cálculo. Sua interface gráfica possibilitou a elaboração de mapas e a visualização das rotas em cada subsetor. Além disso o aplicativo minimizou os percursos e distribuiu os subsetores com distâncias aproximadas. A eficiência das heurísticas que embasaram o aplicativo desenvolvido, foi comprovada através dos testes realizados, os quais obtiveram resultados de boa qualidade.

Scheduling of track inspection and maintenance activities in railroad networks

The U.S. railroad companies spend billions of dollars every year on railroad track maintenance in order to ensure safety and operational efficiency of their railroad networks. Besides maintenance costs, other costs such as train accident costs, train and shipment delay costs and rolling stock maintenance costs are also closely related to track maintenance activities. Optimizing the track maintenance process on the extensive railroad networks is a very complex problem with major cost implications. Currently, the decision making process for track maintenance planning is largely manual and primarily relies on the knowledge and judgment of experts. There is considerable potential to improve the process by using operations research techniques to develop solutions to the optimization problems on track maintenance. In this dissertation study, we propose a range of mathematical models and solution algorithms for three network-level scheduling problems on track maintenance: track inspection scheduling problem (TISP), production team scheduling problem (PTSP) and job-to-project clustering problem (JTPCP). TISP involves a set of inspection teams which travel over the railroad network to identify track defects. It is a large-scale routing and scheduling problem where thousands of tasks are to be scheduled subject to many difficult side constraints such as periodicity constraints and discrete working time constraints. A vehicle routing problem formulation was proposed for TISP, and a customized heuristic algorithm was developed to solve the model. The algorithm iteratively applies a constructive heuristic and a local search algorithm in an incremental scheduling horizon framework. The proposed model and algorithm have been adopted by a Class I railroad in its decision making process. Real-world case studies show the proposed approach outperforms the manual approach in short-term scheduling and can be used to conduct long-term what-if analyses to yield managerial insights. PTSP schedules capital track maintenance projects, which are the largest track maintenance activities and account for the majority of railroad capital spending. A time-space network model was proposed to formulate PTSP. More than ten types of side constraints were considered in the model, including very complex constraints such as mutual exclusion constraints and consecution constraints. A multiple neighborhood search algorithm, including a decomposition and restriction search and a block-interchange search, was developed to solve the model. Various performance enhancement techniques, such as data reduction, augmented cost function and subproblem prioritization, were developed to improve the algorithm. The proposed approach has been adopted by a Class I railroad for two years. Our numerical results show the model solutions are able to satisfy all hard constraints and most soft constraints. Compared with the existing manual procedure, the proposed approach is able to bring significant cost savings and operational efficiency improvement. JTPCP is an intermediate problem between TISP and PTSP. It focuses on clustering thousands of capital track maintenance jobs (based on the defects identified in track inspection) into projects so that the projects can be scheduled in PTSP. A vehicle routing problem based model and a multiple-step heuristic algorithm were developed to solve this problem. Various side constraints such as mutual exclusion constraints and rounding constraints were considered. The proposed approach has been applied in practice and has shown good performance in both solution quality and efficiency.

Optimizing last mile delivery using public transport with multiagent based control

The majority of research work carried out in the field of Operations-Research uses methods and algorithms to optimize the pick-up and delivery problem. Most studies aim to solve the vehicle routing problem, to accommodate optimum delivery orders, vehicles etc. This paper focuses on green logistics approach, where existing Public Transport infrastructure capability of a city is used for the delivery of small and medium sized packaged goods thus, helping improve the situation of urban congestion and greenhouse gas emissions reduction. It carried out a study to investigate the feasibility of the proposed multi-agent based simulation model, for efficiency of cost, time and energy consumption. Multimodal Dijkstra Shortest Path algorithm and Nested Monte Carlo Search have been employed for a two-phase algorithmic approach used for generation of time based cost matrix. The quality of the tour is dependent on the efficiency of the search algorithm implemented for plan generation and route planning. The results reveal a definite advantage of using Public Transportation over existing delivery approaches in terms of energy efficiency.

Architectural-Physical Co-Design of 3D CPUs with Micro-Fluidic Cooling

The performance, energy efficiency and cost improvements due to traditional technology scaling have begun to slow down and present diminishing returns. Underlying reasons for this trend include fundamental physical limits of transistor scaling, the growing significance of quantum effects as transistors shrink, and a growing mismatch between transistors and interconnects regarding size, speed and power. Continued Moore's Law scaling will not come from technology scaling alone, and must involve improvements to design tools and development of new disruptive technologies such as 3D integration. 3D integration presents potential improvements to interconnect power and delay by translating the routing problem into a third dimension, and facilitates transistor density scaling independent of technology node. Furthermore, 3D IC technology opens up a new architectural design space of heterogeneously-integrated high-bandwidth CPUs. Vertical integration promises to provide the CPU architectures of the future by integrating high performance processors with on-chip high-bandwidth memory systems and highly connected network-on-chip structures. Such techniques can overcome the well-known CPU performance bottlenecks referred to as memory and communication wall. However the promising improvements to performance and energy efficiency offered by 3D CPUs does not come without cost, both in the financial investments to develop the technology, and the increased complexity of design. Two main limitations to 3D IC technology have been heat removal and TSV reliability. Transistor stacking creates increases in power density, current density and thermal resistance in air cooled packages. Furthermore the technology introduces vertical through silicon vias (TSVs) that create new points of failure in the chip and require development of new BEOL technologies. Although these issues can be controlled to some extent using thermal-reliability aware physical and architectural 3D design techniques, high performance embedded cooling schemes, such as micro-fluidic (MF) cooling, are fundamentally necessary to unlock the true potential of 3D ICs. A new paradigm is being put forth which integrates the computational, electrical, physical, thermal and reliability views of a system. The unification of these diverse aspects of integrated circuits is called Co-Design. Independent design and optimization of each aspect leads to sub-optimal designs due to a lack of understanding of cross-domain interactions and their impacts on the feasibility region of the architectural design space. Co-Design enables optimization across layers with a multi-domain view and thus unlocks new high-performance and energy efficient configurations. Although the co-design paradigm is becoming increasingly necessary in all fields of IC design, it is even more critical in 3D ICs where, as we show, the inter-layer coupling and higher degree of connectivity between components exacerbates the interdependence between architectural parameters, physical design parameters and the multitude of metrics of interest to the designer (i.e. power, performance, temperature and reliability). In this dissertation we present a framework for multi-domain co-simulation and co-optimization of 3D CPU architectures with both air and MF cooling solutions. Finally we propose an approach for design space exploration and modeling within the new Co-Design paradigm, and discuss the possible avenues for improvement of this work in the future.

Integration of Social Concerns in Collaborative Logistics and Transportation Networks

Part 21: Mobility and Logistics

Improving robustness of rolling stock circulations in rapid transit networks

The rolling stock circulation depends on two different problems: the rolling stock assignment and the train routing problems, which up to now have been solved sequentially. We propose a new approach to obtain better and more robust circulations of the rolling stock train units, solving the rolling stock assignment while accounting for the train routing problem. Here robustness means that difficult shunting operations are selectively penalized and propagated delays together with the need for human resources are minimized. This new integrated approach provides a huge model. Then, we solve the integrated model using Benders decomposition, where the main decision is the rolling stock assignment and the train routing is in the second level. For computational reasons we propose a heuristic based on Benders decomposition. Computational experiments show how the current solution operated by RENFE (the main Spanish train operator) can be improved: more robust and efficient solutions are obtained

Méthode de recherche à grand voisinage pour un problème de tournées de véhicules avec flotte privée et transporteur externe

Dans ce mémoire, nous étudions un problème de tournées de véhicules dans lequel une flotte privée de véhicules n’a pas la capacité suffisante pour desservir les demandes des clients. Dans un tel cas, on fait appel à un transporteur externe. Ce dernier n’a aucune contrainte de capacité, mais un coût est encouru lorsqu’un client lui est affecté. Il n’est pas nécessaire de mettre tous les véhicules de la flotte privée en service si cette approche se révèle plus économique. L’objectif consiste à minimiser le coût fixe des véhicules, puis le coût variable de transport et le coût chargé par le transporteur externe. Notre travail consiste à appliquer la métaheuristique de recherche adaptative à grand voisinage sur ce problème. Nous comparons nos résultats avec ceux obtenus précédemment avec différentes techniques connues sur les instances de Christofides et celles de Golden.

Host and Network Optimizations for Performance Enhancement and Energy Efficiency in Data Center Networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.

Méthode de recherche à grand voisinage pour un problème de tournées de véhicules avec flotte privée et transporteur externe

Dans ce mémoire, nous étudions un problème de tournées de véhicules dans lequel une flotte privée de véhicules n’a pas la capacité suffisante pour desservir les demandes des clients. Dans un tel cas, on fait appel à un transporteur externe. Ce dernier n’a aucune contrainte de capacité, mais un coût est encouru lorsqu’un client lui est affecté. Il n’est pas nécessaire de mettre tous les véhicules de la flotte privée en service si cette approche se révèle plus économique. L’objectif consiste à minimiser le coût fixe des véhicules, puis le coût variable de transport et le coût chargé par le transporteur externe. Notre travail consiste à appliquer la métaheuristique de recherche adaptative à grand voisinage sur ce problème. Nous comparons nos résultats avec ceux obtenus précédemment avec différentes techniques connues sur les instances de Christofides et celles de Golden.

An integrated approach for earthwork allocation, sequencing and routing

Planning techniques for large scale earthworks have been considered in this article. To improve these activities a “block theoretic” approach was developed that provides an integrated solution consisting of an allocation of cuts to fills and a sequence of cuts and fills over time. It considers the constantly changing terrain by computing haulage routes dynamically. Consequently more realistic haulage costs are used in the decision making process. A digraph is utilised to describe the terrain surface which has been partitioned into uniform grids. It reflects the true state of the terrain, and is altered after each cut and fill. A shortest path algorithm is successively applied to calculate the cost of each haul, and these costs are summed over the entire sequence, to provide a total cost of haulage. To solve this integrated optimisation problem a variety of solution techniques were applied, including constructive algorithms, meta-heuristics and parallel programming. The extensive numerical investigations have successfully shown the applicability of our approach to real sized earthwork problems.

The Cache Inference Problem and its Application to Content and Request Routing

In many networked applications, independent caching agents cooperate by servicing each other's miss streams, without revealing the operational details of the caching mechanisms they employ. Inference of such details could be instrumental for many other processes. For example, it could be used for optimized forwarding (or routing) of one's own miss stream (or content) to available proxy caches, or for making cache-aware resource management decisions. In this paper, we introduce the Cache Inference Problem (CIP) as that of inferring the characteristics of a caching agent, given the miss stream of that agent. While CIP is insolvable in its most general form, there are special cases of practical importance in which it is, including when the request stream follows an Independent Reference Model (IRM) with generalized power-law (GPL) demand distribution. To that end, we design two basic "litmus" tests that are able to detect LFU and LRU replacement policies, the effective size of the cache and of the object universe, and the skewness of the GPL demand for objects. Using extensive experiments under synthetic as well as real traces, we show that our methods infer such characteristics accurately and quite efficiently, and that they remain robust even when the IRM/GPL assumptions do not hold, and even when the underlying replacement policies are not "pure" LFU or LRU. We exemplify the value of our inference framework by considering example applications.

Facets of the polytope of the asymmetric travelling salesman problem with replenishment arcs

The Asymmetric Travelling Salesman Problem with Replenishment Arcs (RATSP) is a new class of problems arising from work related to aircraft routing. Given a digraph with cost on the arcs, a solution of the RATSP, like that of the Asymmetric Travelling Salesman Problem, induces a directed tour in the graph which minimises total cost. However the tour must satisfy additional constraints: the arc set is partitioned into replenishment arcs and ordinary arcs, each node has a non-negative weight associated with it, and the tour cannot accumulate more than some weight limit before a replenishment arc must be used. To enforce this requirement, constraints are needed. We refer to these as replenishment constraints.

In this paper, we review previous polyhedral results for the RATSP and related problems, then prove that two classes of constraints developed in V. Mak and N. Boland [Polyhedral results and exact algorithms for the asymmetric travelling salesman problem with replenishment arcs, Technical Report TR M05/03, School of Information Technology, Deakin University, 2005] are, under appropriate conditions, facet-defining for the RATS polytope.