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This thesis deals with a real world problem of an optimal planning of transferring goods between stores of a certain retail company. The aim is to propose a system which, based on customer orders and current stock items availability, should be capable of devising an optimal plan. In this thesis, following a thorough analysis of the problem, there is a formalised problem of automated logistics. After a brief overview of existing approaches in the area of logistics problem solving, there are subsequently designed solution methods based on programming with limited conditions and mixed integer programming. Both methods are compared to each other experimentally, by taking into account the quality of the found solution and the methods' efficiency.

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Dynamical network systems are complex interconnected systems useful to describe many real world problems. The advances in information technology has led the current trend towards connecting more and more systems, creating "intelligent" systems, where the intelligence originates in the scale and complexity of the network. With the growing scale of networked systems comes also higher demands on performance and continuous availability and this creates the need for optimization and control of network systems. This thesis makes four important contributions in this area. In the first contribution, we consider a collaborative road freight transportation system. An efficiency measure for the road utilization in collaborative transportation scenarios is introduced, which evaluates the performance of collaboration strategies in comparison to an optimal central planner. The efficiency measure is used to study a freight transport simulation in Germany and taxi trips using real data from New York City. This is followed by a study of the optimal idling locations for trucks, and the optimal locations for distribution centers. These locations are then exploited in a simulation of a realistic collaborative freight transport system. The second contribution studies the important problem of gathering data that are distributed among the nodes in an anonymous network, i.e., a network where the nodes are not endowed with unique identifies. Two specific tasks are considered: to estimate the size of the network, and to aggregate the distribution of local measurements generated by the nodes. We consider a framework where the nodes require anonymity and have restricted computational resources. We propose probabilistic algorithms with low resource requirements, that quickly generate arbitrarily accurate estimates. For dynamical networks, we improve the accuracy through a regularization term which captures the trade-off between the reliability of the gathered data and a-priori assumptions for the dynamics. In the third contribution, a peer-to-peer network is utilized to improve a live-streaming media application. In particular, we study how an overlay network, constructed from simple preference functions, can be used to build efficient topologies that reduce both network latency and interruptions. We present necessary and sufficient convergence conditions, as well as convergence rate estimates, and demonstrate the improvements for a real peer-to-peer video streaming application. The final contribution is a distributed optimization algorithm. We consider a distributed multi-agent optimization problem of minimizing the sum of convex objective functions. A decentralized optimization algorithm is introduced, based on dual decomposition, together with the subgradient method for finding the optimal solution. The convergence rate is analyzed for different step size rules, constant and time-varying communication delays, and noisy communication channels. / Dynamiska nätverkssystem är komplexa sammankopplade system med många praktiska tillämpningar. Den snabba utvecklingen inom informationsteknologin har drivit trenden att sammankoppla större och större system till nätverk av "intelligenta" system, där intelligensen kommer från komplexiteten av nätverken. Med den ökande storleken på nätverkssystemen kommer också ökade krav på dess prestanda och tillgänglighet, vilket är drivkraften bakom utvecklingen av optimering och styrning av nätverkssystem. Den här avhandlingen presenterar fyra viktiga bidrag inom detta område. Det första bidraget handlar om kooperativ lastbilstransport. Först introduceras ett mått som mäter effektiviteten i systemet jämfört med en central planerare. Detta mått används sedan för att utvärdera vinsterna med kooperativa transporter, men används också för att utvärdera taxiförarnas vägval med verkliga data från New York City. Detta följs av en studie av de optimala vänteplatserna för lastbilar och de optimal placeringarna av distributionscentraler. Dessa positioner används sedan för att förbättra transportprestandan i ett kooperativt transportsystem. I det andra bidraget studeras informationsaggregering i anonyma nätverkssystem, det vill säga nätverk där noderna saknar unika identiteter. Två specifika problem hanteras: att estimera storleken på nätverket, och att sammanställa fördelningen av lokala mätvärden i nätverket. Noderna i detta nätverk kräver anonymitet, men antas också ha strikt begränsad beräkningskapacitet. Vi presenterar stokastiska algoritmer med låga beräkningskrav, som dessutom har snabb konvergens och som kan justeras till att ge godtycklig precision. För dynamiska nätverk förbättras prestandan genom att en regulariseringsterm används för att väga observerad data mot förväntat beteende hos systemet. I tredje bidraget analyseras ett peer-to-peer nätverk för direktsänd videodistribution. Speciellt studeras konvergensen av nätverkstopologin som genereras från lokala preferensfunktioner, och hur resultaten kan används för att minska fördröjningarna och avbrotten under videouppspelning. Vi ger nödvändiga och tillräckliga villkor för konvergens, samt karakteriserar gränsvärden för hur snabbt användare kan ansluta eller lämna nätverket utan att påverka prestandan. Det sista bidraget är en distribuerad optimeringsalgoritm. Problemet består i att minimera summan av konvexa funktioner för varje nod i ett nätverk. En decentraliserad optimeringsalgoritm presenteras som baseras på det duala optimeringsproblemet tillsammans med subgradient-metoden. Konvergenshastigheten analyseras för olika val av steglängder, konstanta samt tidsberoende kommunikationsfördröjningar och brusiga kommunikationskanaler. / <p>QC 20161020</p>

During the two last decades, topology optimization has grown to be an accepted and used method to produce conceptual designs. Topology optimization is traditionally carried out on a component level, but in this project, the possibility to apply it to airframe design on a full scale aeroplane model is evaluated. The project features a conceptual flying-wing design on which the study is to be carried out. Inertia Relief is used to constrain the aeroplane instead of traditional single point constraints with rigid body motion being suppressed by the application of accelerations instead of traditional forces and moments. The inertia relief method utilized the inertia of the aeroplane to achieve a state of quasi-equilibrium such that static finite element analysis can be carried out. Two load cases are used: a steep pitch-up manoeuvre and a landing scenario. Aerodynamic forces are calculated for the pitch-up load case via an in-house solver, with the pressure being mapped to the finite element mesh via a Matlab-script to account for different mesh sizes. Increased gravitational loads are used in the landing load case to simulate the dynamic loading caused in a real landing scenario, which is unable to be accounted for directly in the topology optimization. It can be concluded that the optimization is unable to account for one of the major design limitations: buckling of the outer skin. Approaches to account for the buckling of the outer skin are introduced and analysed, with a focus on local compression constraints throughout the wing. The compression constraints produce some promising results but are not without major drawbacks and complications. In general, a one-step topology optimization to produce a mature conceptual airframe design is not possible with optimization algorithms today. It may be possible to adopt a multiple-step optimization approach utilizing topology optimization with following size and shape optimization to achieve a design, which could be expanded on in a future project.

Water quality evaluation is a global concern due to its effect on public health. Different procedures can be implemented to evaluate specific standards of water quality. DNA extraction to characterize the microbial community in the water distribution systems is important. To optimize the DNA extraction process the effect of residual chlorine and water composition was tested. The results exposed the limited effect of the samples dechlorination. Total cell number effect can be varied according to water quality. Also, the study indicated the possible inhibitory effect of the rust on the DNA extraction from drinking water samples.