Many real-world vehicle routing problems are dynamic optimization problems, with customer requests arriving over time, requiring a repeated reoptimization. In this paper, we consider a dynamic vehicle routing problem where one additional customer arrives at a beforehand unknown location when the vehicles are already under way. Our objective is to maximize the probability that the additional customer can be integrated into one of the otherwise fixed tours without violating time constraints. This is achieved by letting the vehicles wait at suitable locations during their tours, thus influencing the position of the vehicles at the time when the new customer arrives. For the cases of one and two vehicles, we derive theoretical results about the best waiting strategies. The general problem is shown to be NP-complete. Several deterministic waiting strategies and an evolutionary algorithm to optimize the waiting strategy are proposed and compared empirically. It is demonstrated that a proper waiting strategy can significantly increase the probability of being able to service the additional customer, at the same time reducing the average detour to serve that customer.

We present an online distributed algorithm, the Causation Logging Algorithm (CLA), in which Autonomous Systems (ASes) in the Internet individually report route oscillations/flaps they experience to a central Internet Routing Registry (IRR). The IRR aggregates these reports and may observe what we call causation chains where each node on the chain caused a route flap at the next node along the chain. A chain may also have a causation cycle. The type of an observed causation chain/cycle allows the IRR to infer the underlying policy routing configuration (i.e. the system of economic relationships and constraints on route/path preferences). Our algorithm is based on a formal policy routing model that captures the propagation dynamics of route flaps under arbitrary changes in topology or path preferences. We derive invariant properties of causation chains/cycles for ASes which conform to economic relationships based on the popular Gao-Rexford model. The Gao-Rexford model is known to be safe in the sense that the system always converges to a stable set of paths under static conditions. Our CLA algorithm recovers the type/property of an observed causation chain of an underlying system and determines whether it conforms to the safe economic Gao-Rexford model. Causes for nonconformity can be diagnosed by comparing the properties of the causation chains with those predicted from different variants of the Gao-Rexford model.

Abstract Home Health Care (HHC) is a health care service delivered by sending caregivers such as nurses or personal support workers (PSW) to visit patients in their homes. The assignment of patients to nurses as well as the sequencing of patients for each nurse is called the Home Health Care Scheduling and Routing Problem (HHCSRP). This thesis proposes a heuristic approach to solve HHCSRP to which it is hard and even impossible to obtain an optimal solution for relative larger instances in a reasonable amount of computational time by using an exact algorithm as HHCSRP is NP hard. In the approach, this thesis developed and contributed a heuristic partition method to partition patients into a number of single nurse groups. The computational test result shows that the proposed approach can achieve good solutions which remain within 5% of the commercial solver CPLEX’s best solution using an acceptable solution time on all test instances.

Que le phénomène découle d’une prise de conscience des conséquences sur l’environnement, d’une opportunité économique ou d’une question de réputation et de commerce, la réduction des émissions de gaz à effets de serre est récemment devenue un objectif de premier plan. Les individus, les entreprises et les gouvernements effectuent un effort important pour réduire la dépense énergétique de multiples secteurs d’activité. Parallèlement, les technologies de l’information et de la communication sont de plus en plus présentes dans la plupart des activités humaines et l’on a estimé que 2% des émissions de gaz à effets de serre pouvaient leur être attribuées, cette proportion atteignant 10 % dans les pays fortement industrialisés [1, 2]. Si ces chiffres paraissent raisonnables aujourd’hui, ils sont certainement appelés à croître à l’avenir. À l’heure du cloud computing, les infrastructures de calcul et de communication demandent de plus en plus de performance et de disponibilité et imposent l’utilisation de matériels puissants et engendrant une consommation d’énergie importante du fait de leur fonctionnement direct, mais aussi à cause du refroidissement qu’ils nécessitent. En outre, les contraintes de disponibilité imposent une conception d’architectures redondantes et dimensionnées sur une charge crête. Les infrastructures sont donc souvent sous-utilisées et adapter leur niveau de performance à la charge effectivement constatée constitue une piste d’optimisation prometteuse à divers niveaux. Si l’on adopte un strict point de vue environnemental, l’objectif du Green Networking consiste à réduire le volume d’émissions de gaz à effets de serre dues au processus de communication. L’utilisation de sources d’énergie renouvelables ou d’électronique de faible consommation (par exemple asynchrone) constituent des pistes évidentes d’amélioration. / The reduction of power consumption in communication networks has become a key issue for both the Internet Service Providers (ISP) and the research community. Ac- cording to different studies, the power consumption of Information and Communication Technologies (ICT) varies from 2% to 10% of the worldwide power consumption [1, 2]. Moreover, the expected trends for the future predict a notably increase of the ICT power consumption, doubling its value by 2020 [2] and growing to around 30% of the worldwide electricity demand by 2030 according to business-as-usual evaluation scenarios [15]. It is therefore not surprising that researchers, manufacturers and network providers are spending significant efforts to reduce the power consumption of ICT systems from dif- ferent angles. To this extent, networking devices waste a considerable amount of power. In partic- ular, their power consumption has always been increased in the last years, coupled with the increase of the offered performance [16]. Actually, power consumption of network- ing devices scales with the installed capacity, rather than the current load [17]. Thus, for an ISP the network power consumption is practically constant, unrespectively to traffic fluctuations. However, actual traffic is subject to strong day/night oscillations [3]. Thus, many devices are underutilized, especially during off-peak hours when traffic is low. This represents a clear opportunity for saving energy, since many resources (i.e., routers and links) are powered on without being fully utilized. In this context, resource consolidation is a known paradigm for the reduction of the power consumption. It consists in having a carefully selected subset of network devices entering a low power state, and use the rest to transport the required amountof traffic.

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The purpose of this dissertation is to develop models and solution approaches to identify the critical hierarchies of railroad and surface transportation network infrastructures, and to facilitate re-routing options that will be necessary for traffic management decision makings in the event of a disaster. We focus on building mathematical models for routing/re-routing of traffic considering the congestion effects which are obvious in the disrupted networks due to disaster. Based on these models, the critical hierarchies of infrastructures are determined. For railroad, we develop two different models: the first one considers ‘unit’ train re-routing and the other one considers Train Design approach. For intermodal system, the optimization model facilitates optimal re-routing of traffic using three surface transportation modes: highway, railway and waterway, considering the congestion characteristics of each mode. For the first model of railroad routing, the optimization model optimally routes unit trains based on a minimum cost network flow formulation with nonlinear objective function. The nonlinear objective function is approximated with a piece-wise linear function to make the model computationally tractable. The second model, known as Train Design optimization, is a highly combinatorial and complex optimization problem. The developed model’s computational complexity suggests us to use heuristic solution procedures. We develop a special heuristic algorithm to route the traffic in the congested network. In this heuristic procedure, we divide the problem into two sub-problems (SPs): SP-1 is termed as Block-to-Train Assignment (BTA) problem, and SP-2 is termed as Train Routing (TR) problem. BTA problem provides a feasible solution that includes the minimum number of required trains with the pick-up and drop-off points of the blocks carried by these trains, and TR problem ensures the optimal routing of these trains. Similar to railroad, an optimization model is developed for optimal routing/rerouting of traffic using the intermodal network. It is a mixed integer programming (MIP) problem, which is not practical to solve for real-world problem instances within reasonable amount of time. Linear relaxation to this model provides a very good lower bound closer to optimal solution. Therefore, we implemented our case-study for a realworld intermodal transportation system of five U.S. states.

<p> To provide a logical framework for the comparison of various methods of kinematic flood routing a general method of kinematic flood routing is developed.</p> <p> After presenting the general framework, the properties of the numerical model are investigated by: l. Algebraic examination of the finite difference scheme. 2.Numerical experiments using a high speed digital computer. 3. Comparison of the kinematic flood routing results with results of simulations using the complete one dimensional dynamic representation.</p> <p> Particular facets of the numerical kinematic model that were studied included: 1. The stability of the numeric schematizations. 2. The degree of approximation with the finite difference system. 3. The applicability of kinematic methods to unsteady flow systems. 4. Methods of extending the kinematic solutions to predict attenuation as well as translation of the flood wave through the channel systems. </p> <p> The results indicate that kinematic flood routing methods differ primarily in the point about which the finite difference equation is formulated, hereafter termed the nucleus, and that the general framework is capable of emulating such methods as the Muskinghum Method, other non-linear kinematic methods and reservoir routing. By varying the location of the nucleus the stability and degree of approximation is significantly altered. This results in the outflow hydrograph being sensitive to the location of the nucleus and the size of the finite difference steps.</p> <p> To facilitate further research and application of the methods outlined in the thesis, a computer program was developed to enable kinematic flood routing to be performed in a natural channel with arbitrary geometry. Furthermore, the data is compatible with a program that is capable of performing a flood routing analysis using a numerical solution of the complete Saint-Venant equations. Documentation of the computer program for kinematic analysis is included with this thesis.</p> / Thesis / Master of Engineering (MEngr)

The Internet and other large computer networks have become an integral part of numerous daily processes. Security at the network layer is necessary to maintain infrastructure survivability in the case of cyber attacks aimed at routing protocols. In order to minimize undesired overhead associated with added security at this level, the notion of selective security is proposed. This thesis identifies elements in network topologies that are most important to the survivability of the network. The results show that the strategic placement of network security at critical elements will improve overall network survivability without the necessity of universal deployment.

Interlibrary Loan entails obtaining copies of library materials not found in the library's collection on behalf of the library's patrons (borrowing), as well as providing copies of library materials requested by other libraries (lending). The dynamic nature of today's library environment is well illustrated by the rapid changes occurring in the role of interlibrary loan. The vision statement of the University of Central Florida Library is: The library performs a central role of adding value to information for the academic community by creatively improving and providing information resources and services. The library strives to create an environment that encourages the pursuit of intellectual endeavors and the creation of new knowledge. In an endeavor to fulfill this vision, the Interlibrary Loan Department at the UCF main library wants to set up a document delivery service within the UCF main campus in order to facilitate research efforts on campus. The document delivery service will include delivery and pickup of library materials for ILL requests by faculty online (via computers). In this study, we build a Traveling Salesperson model for obtaining a routing sequence for the document delivery service. Next, we analyze this model in order to check the feasibility of the routing sequence in presence of demand (delivery and pickup) by simulating the demand over the route using computer simulation software. We conclude by validating the model under given conditions and providing route sequence recommendations in the case of extreme demands.

Devices taking part in mobile ad hoc networks (MANET) co-operate with each other to route packets by strictly adhering to the ad hoc routing protocol in use. Malicious nodes taking part in co-operative routing can launch a wide variety of attacks to reduce the utility of MANETs. The aim of secure routing protocols is to ensure that MANETs can continue to function even in the face of malicious nodes. Secure routing protocols should have measures to dissuade attackers by detecting inconsistencies, identifying the perpetrator responsible for the inconsistency, and provide means to inhibit the role of misbehaving nodes. Most existing secure routing protocols try to achieve only first step, viz., detection of inconsistencies. This dissertation research investigates and proposes efficient strategies that substantially enhance the scope of assurances provided by secure MANET routing protocols while keeping the overhead low.