The behaviour of a large, distributed system is inherently complex. One step towards making this behaviour more understandable to a user involves instrumenting the system and collecting data about its execution. We can model the data as traces (representing various sequential entities in the system such as single-threaded processes) that contain both events local to the trace and communication events involving another trace. Visualizing this data provides a modest benefit to users as it makes basic interactions in the system clearer and, with some user effort, more complex interactions can be determined. Unfortunately, visualization by itself is not an adequate solution, especially for large numbers of events and complex interactions among traces. A search facility has the ability to make this event data more useful. Work has been done previously on various frameworks and algorithms that could form the core of such a search facility; however, various shortcomings in the completeness of the frameworks and in the efficiency of the algorithms resulted in an inconsistent, incomplete, and inefficient solution. This thesis takes steps to remedy this situation. We propose a provably-complete framework for determining precedence between sets of events and propose additions to a previous pattern-specification language so it can specify a wider variety of search patterns. We improve the efficiency of the existing search algorithm, and provide a new, more efficient, algorithm that processes a pattern in a fundamentally different way. Furthermore, the various proposed improvements have been implemented and are analysed empirically.

The behaviour of a large, distributed system is inherently complex. One step towards making this behaviour more understandable to a user involves instrumenting the system and collecting data about its execution. We can model the data as traces (representing various sequential entities in the system such as single-threaded processes) that contain both events local to the trace and communication events involving another trace. Visualizing this data provides a modest benefit to users as it makes basic interactions in the system clearer and, with some user effort, more complex interactions can be determined. Unfortunately, visualization by itself is not an adequate solution, especially for large numbers of events and complex interactions among traces. A search facility has the ability to make this event data more useful. Work has been done previously on various frameworks and algorithms that could form the core of such a search facility; however, various shortcomings in the completeness of the frameworks and in the efficiency of the algorithms resulted in an inconsistent, incomplete, and inefficient solution. This thesis takes steps to remedy this situation. We propose a provably-complete framework for determining precedence between sets of events and propose additions to a previous pattern-specification language so it can specify a wider variety of search patterns. We improve the efficiency of the existing search algorithm, and provide a new, more efficient, algorithm that processes a pattern in a fundamentally different way. Furthermore, the various proposed improvements have been implemented and are analysed empirically.

Today in most design offices the practice when designing infrastructure is to adopt a trial-and-error based approach. This means that one solution to the problem is evaluated and based on the results the design is altered. This process is then repeated until satisfactory results have been achieved. This is an iterative process and in this project, a software has been developed as a tool for the practicing engineer to use for preliminary design. The software carries out this iterative process and optimizes the solution using algorithms. The software is developed to evaluate road traffic composite bridges according to the Eurocodes. The bridges are made up from two main steel beams with a concrete deck on top. The software has then been used in a number of different studies in order to evaluate its potential as a preliminary design method. The results show that this is a viable tool for preliminary designs, with the drawback that, each iteration is computationally expensive and therefore, optimization of a real-case problem takes a lot of time in order to find the optimal design. / I dagsläget använder de flesta konstruktionsföretagen sig av en iterativ process när de konstruerar infrastruktur. Man utvärderar en lösning och beroende av resultatet så justeras lösningen och utvärderas på nytt, detta återupprepas tills en tillfredsställande lösning har erhållits. Detta är en iterativ process och i samband med detta arbete så har en mjukvara utvecklats som ett verktyg till konstruktören. Mjukvaran utför det iterativa arbetet och optimerar konstruktionen med hjälp av optimeringsalgoritmer. Programmet utvärderar vägbroar av en samverkanskonstruktion i form av två stålbalkar med en betongplatta ovanpå, beräkningarna sker enligt Eurokoderna. Programmet har använts för att utvärdera det här arbetssättets potential vid anbudsskede i projekt. Resultaten visar att det finns potential för detta med nackdelen att varje iteration är tidskrävande vilket gör att optimering av ett realistiskt projekt tar lång tid.

Piling is expensive but often necessary when building large structures, for example bridges. Some pile types, such as steel core piles, are very costly and it is therefore of great interest to keep the number piles in a pile group to a minimum. This thesis deals with optimization of pile groups with respect to placement, batter and angle of rotation in order to minimize the number of piles. A program has been developed, where two optimization algorithms named Genetic Algorithm and Direct Search, and four objective functions have been used. These have been tested and compared to find the most suitable for pile group optimization. Three real cases, two bridge supports and one culvert, have been studied, using the program.  It has been difficult to draw any clear conclusions since the results have been ambiguous. This is probably because only three cases have been tested and the results are very problemdependent.The outcome depends, for example, on the starting guess and settings for the optimization. However, the results show that the Genetic Algorithm is somewhat more robust in its ability to remove piles than Direct Search and is therefore to prefer in pile group optimization.

In this thesis we propose four new methods for solving constrained global optimization problems. The first proposed algorithm is a differential evolution (DE) algorithm using penalty functions for constraint handling. The second algorithm is based on the first DE algorithm but also incorporates a filter set as a diversification mechanism. The third algorithm is also based on DE but includes an additional local refinement process in the form of the pattern search (PS) technique. The last algorithm incorporates both the filter set and PS into the DE algorithm for constrained global optimization. The superiority of feasible points (SFP) and the parameter free penalty (PFP) schemes are used as constraint handling mechanisms. The new algorithms were numerically tested using two sets of test problems and the results where compared with those of the genetic algorithm (GA). The comparison shows that the new algorithms outperformed GA. When the new methods are compared to each other, the last three methods performed better than the first method i.e. the DE algorithm. The new algorithms show promising results with potential for further research. Keywords: constrained global optimization, differential evolution, pattern search, filter method, penalty function, superiority of feasible points, parameter free penalty. ii

Ca2+, a signal for death and life, is closely involved in the regulation of numerous important cellular events. Ca2+ carries out its function through its binding to Ca2+-receptors or Ca2+-binding proteins. The EF-hand protein, with a helix-loop-helix Ca2+-binding motif, constitutes one of the largest protein families. To facilitate our understanding of the role of Ca2+ in biological systems (denoted as calciomics) using genomic information, an improved pattern search method (http://www.chemistry.gsu.edu/faculty/Yang/Calciomics.htm) for the identification of EF-hand and EF-like Ca2+-binding proteins was developed. This fast and robust method allows us to analyze putative EF-hand proteins at the genome-wide level and further visualize the evolutionary scenario of the EF-hand protein family. This prediction method further enables us to locate a putative viral EF-hand Ca2+-binding motif within the rubella virus nonstructural protease that cleaves the nonstructural protein precursor into two active replicase components. A novel grafting approach has been used to probe the metal-binding properties of this motif by engineering the predicted 12-residue Ca2+-coordinating loop into a non-Ca2+-binding scaffold protein, CD2 domain 1. Structural and conformational studies were further performed on a purified, bacterially-expressed NS protease minimal metal-binding domain spanning the Zn2+- and EF-hand Ca2+-binding motif. It was revealed that Ca2+ binding induced local conformational changes and increased thermal stability. Furthermore, functional studies were carried out using RUB infectious cDNA clone and replicon constructs. Our studies have shown that the Ca2+ binding loop played a structural role in the NS protease and was specifically required for optimal stability under physiological conditions. In addition, we have predicted and characterized a calmodulin-binding domain in the gap junction proteins connexin43 and connexin44. Peptides encompassing the CaM binding motifs were synthesized and their ability to bind CaM was determined using various biophysical approaches. Transient expression in HeLa cells of two mutant Cx43-EYFP constructs without the putative CaM-binding site eliminated the Ca2+-dependent inhibition of gap junction permeability. These results provide the first direct evidence that CaM binds to a specific region of the ubiquitous gap junction protein Cx43 and Cx44 in a Ca2+-dependent manner, providing a molecular basis for the well-characterized Ca2+-dependent inhibition of Cx43-containing gap junctions.

Recent advances in the field of computational intelligence have led to a numberof promising optimization algorithms. These algorithms have the potential to findoptimal or near-optimal solutions to complex problems within a reasonable timeframe. Structural optimization is a research field where such algorithms are appliedto optimally design structures. Although a significant amount of research has been published in the field ofstructural optimization since the 1960s, little of the research effort has been utilizedin structural design practice. One reason for this is that only a small portion ofthe research targets real-world applications. Therefore there is a need to conductresearch on cost optimization of realistic structures, particularly large structureswhere significant cost savings may be possible. To address this need, a software application for cost optimization of beam bridgeswas developed. The software application was limited to road bridges in concretethat are straight and has a constant width of the bridge deck. Several simplificationswere also made to limit the scope of the thesis. For instance, a rough design ofthe substructure was implemented, and the design of some structural parts wereneglected. This thesis introduces the subject of cost optimization, treats fundamentaloptimization theory, explains how the software application works, and presents acase study that was carried out to evaluate the application. The result of the case study suggests a potential for significant cost savings. Yet,the speeding up of the design process is perhaps the major benefit that should inclinedesigners to favor optimization. These findings mean that current optimizationalgorithms are robust enough to decrease the cost of beam bridges compared to aconventional design. However, the software application needs several improvementsbefore it can be used in a real design situation, which is a topic for future research. / Nya framsteg inom forskningen har lett till ett antal lovande optimeringsalgoritmer.Dessa algoritmer har potentialen att hitta optimala eller nästan optimala lösningartill komplexa problem inom rimlig tid. Strukturoptimering är ett forskningsområdedär dessa algoritmer tillämpas för att dimensionera konstruktioner på ett optimaltsätt. Även om en betydande mängd forskning har publicerats inom området strukturoptimeringsedan 1960-talet, så har endast lite av forskningsinsatserna kommit tillanvändning i praktiken. Ett skäl till detta är att endast en liten del av forskningenär inriktad mot verklighetsförankrade tillämpningar. Därför finns det ett behov avatt bedriva forskning på kostnadsoptimering av realistiska konstruktioner, särskiltstora konstruktioner där betydande kostnadsbesparingar kan vara möjligt. För att möta detta behov har ett datorprogram för kostnadsoptimering avbalkbroar utvecklats. Programmet begränsades till vägbroar i betong som är rakaoch har en konstant bredd. Flera förenklingar gjordes också för att begränsaomfattningen av arbetet. Till exempel implementerades en grov dimensionering avunderbyggnaden, och dimensioneringen av vissa komponenter försummades helt ochhållet. Detta examensarbete presenterar ämnet kostnadsoptimering, behandlar grundläggandeoptimeringsteori, förklarar hur programmet fungerar, och presenterar enfallstudie som genomfördes för att utvärdera programmet. Resultatet av fallstudien visar en potential för betydande kostnadsbesparingar.Trots det så är tidsbesparingarna i dimensioneringsprocessen kanske den störstafördelen som borde locka konstruktörer att använda optimering. Dessa upptäckterinnebär att aktuella optimeringsalgoritmer är tillräckligt robusta för att minskakostnaden för balkbroar jämfört med en konventionell dimensionering. Dock måsteprogrammet förbättras på flera punkter innan det kan användas i en verklig dimensioneringssituation,vilket är ett ämne för framtida forskning.

This dissertation is concerned with the unconstrained global optimization of nonlinear problems. These problems are not easy to solve because of the multiplicity of local and global minima. In this dissertation, we first study the pattern search method for local optimization. We study the pattern search method numerically and provide a modification to it. In particular, we design a new pattern search method for local optimization. The new pattern search improves the efficiency and reliability of the original pattern search method. We then designed two simulated annealing algorithms for global optimization based on the basic features of pattern search. The new methods are therefore hybrid. The first hybrid method is the hybrid of simulated annealing and pattern search. This method is denoted by MSA. The second hybrid method is a combination of MSA and the multi-level single linkage method. This method is denoted by SAPS. The performance of MSA and SAPS are reported through extensive experiments on 50 test problems. Results indicate that the new hybrids are efficient and reliable.

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In this work we present a new tool for the convergence analysis of numerical optimization methods. It is based on the concepts of the Clarke derivative and set-valued mappings. Our goal is to apply this tool to minimization problems with non-smooth and noisy objective functions. After deriving a necessary condition for minimizers of such functions, we examine two unconstrained optimization routines. First, we prove new convergence theorems for Implicit Filtering and General Pattern Search. Then we show how these results can be used in practice, by executing some numerical computations. / Master of Science