This Master's thesis is focused on the purchase of XYZ Company, Ltd. The first section provides theoretical knowledge necessary to understand the issue, in the second part is analysis of business processes performed. Based on the observed conditions were evaluated insufficient process – supplier evaluation. That is why a new complete procedure for the evaluation of the suppliers was suggested

The thesis is focused on analysis and optimization of processes in a company realizing software projects. Its aim is to find deficiencies in the process of realization of an individual customer requirement and to design improvements. According to the analysis of the process of requirement realization, the deficiencies were analysed from which the most important were selected and used for designing optimization of this process.

This diploma thesis deals with application of quality tools in production plant. Theoretical part deal with history of quality, current situation in quality management and describe some of quality tools. In practical part will be applied some of described quality tools. Some of them are already implemented in production but only partially and they are not used in full for more flexible and efficient production. Conclusions and results of this diploma thesis should prove that if we are using these tools in full, we can decrease extra cost in production.

This diploma thesis is engaged in a system design, which is created to be used for warranty claims data collection. The issue of the second part of this document is the implementation of the system and the description of the next analyse for warranty claims costs minimalisation.

The master’s thesis describes and analyzes the current reservation system of testing devices in Honeywell, spol. s r.o. – HTS CZ, o.z. divize ACS. The system is analyzed by using Six Sigma methods and proposes for improving the current system are prepared. These improvements should improve the functionality of the reservation system and possible savings. Appropriate metrics for measuring and evaluating the functionality of the system are designed.

The main goal of a study is to rationalize organization of production and material handling in company AVL Moravia s.r.o. via material flow intensity analysis. Analysis results in suggesting new organization of production and economical rating of the suggestion.

The thesis deals with a proposal to change the production process by eliminating the redundant control activities. The first part of the thesis presents various possible theoretical approaches for this issue. It is followed by familiarisation with the concerned production company. The second part is the analytical part where the carried out activities of a particular automotive production unit are identified. These control activities are investigated and then either omitted or authorized. Finally the root causes for the fact that those activities have not already been eliminated are found.

Multi-objective decision-making is critical for everyday tasks and engineering problems. Finding the perfect trade-off to maximize all the solution's criteria requires a considerable amount of experience or the availability of a significant number of resources. This makes these decisions difficult to achieve for expensive problems such as engineering. Most of the time, to solve such expensive problems, we are limited by time, resources, and available expertise. Therefore, it is desirable to simplify or approximate the problem when possible before solving it. The state-of-the-art approach for simplification is model-based or surrogate-based optimization. These approaches use approximation models of the real problem, which are cheaper to evaluate. These models, in essence, are simplified hypotheses of cause-effect relationships, and they replace high estimates with cheap approximations. In this thesis, we investigate surrogate models as wrappers for the real problem and apply \gls{moea} to find Pareto optimal decisions. The core idea of surrogate models is the combination and stacking of several models that each describe an independent objective. When combined, these independent models describe the multi-objective space and optimize this space as a single surrogate hypothesis - the surrogate compositional model. The combination of multiple models gives the potential to approximate more complicated problems and stacking of valid surrogate hypotheses speeds-up convergence. Consequently, a better result is obtained at lower costs. We combine several possible surrogate variants and use those that pass validation. After recombination of valid single objective surrogates to a multi-objective surrogate hypothesis, several instances of \gls{moea}s provide several Pareto front approximations. The modular structure of implementation allows us to avoid a static sampling plan and use self-adaptable models in a customizable portfolio. In numerous case studies, our methodology finds comparable solutions to standard NSGA2 using considerably fewer evaluations. We recommend the present approach for parameter tuning of expensive black-box functions.:1 Introduction 1.1 Motivation 1.2 Objectives 1.3 Research questions 1.4 Results overview 2 Background 2.1 Parameter tuning 2.2 Multi-objective optimization 2.2.1 Metrics for multi-objective solution 2.2.2 Solving methods 2.3 Surrogate optimization 2.3.1 Domain-specific problem 2.3.2 Initial sampling set 2.4 Discussion 3 Related Work 3.1 Comparison criteria 3.2 Platforms and frameworks 3.3 Model-based multi-objective algorithms 3.4 Scope of work 4 Compositional Surrogate 4.1 Combinations of surrogate models 4.1.1 Compositional Surrogate Model [RQ1] 4.1.2 Surrogate model portfolio [RQ2] 4.2 Sampling plan [RQ3] 4.2.1 Surrogate Validation 4.3 Discussion 5 Implementation 5.1 Compositional surrogate 5.2 Optimization orchestrator 6 Evaluation 6.1 Experimental setup 6.1.1 Optimization problems 6.1.2 Optimization search 6.1.3 Surrogate portfolio 6.1.4 Benchmark baseline 6.2 Benchmark 1: Portfolio with compositional surrogates. Dynamic sampling plan 6.3 Benchmark 2: Inner parameters 6.3.1 TutorM parameters 6.3.2 Sampling plan size 6.4 Benchmark 3: Scalability of surrogate models 6.5 Discussion of results 7 Conclusion 8 Future Work A Appendix A.1 Benchmark results on ZDT DTLZ, WFG problems

A mobile ad hoc network (MANET) is an infrastructure-less multi-hop network where each node communicates with other nodes directly or indirectly through intermediate nodes. Thus, all nodes in a MANET basically function as mobile routers participating in some routing protocol required for deciding and maintaining the routes. Since MANETs are infrastructure-less, self-organizing, rapidly deployable wireless networks, they are highly suitable for applications such as military tactical operations, search and rescue missions, disaster relief operations, and target tracking. Building such ad-hoc networks poses a significant technical challenge because of energy constraints and specifically in relation to the application of wireless network protocols. As a result of its highly dynamic and distributed nature, the routing layer within the wireless network protocol stack, presents one of the key technical challenges in MANETs. In particular, energy efficient routing may be the most important design criterion for MANETs since mobile nodes are powered by batteries with limited capacity and variable recharge frequency, according to application demand. In order to conserve power it is essential that a routing protocol be designed to guarantee data delivery even should most of the nodes be asleep and not forwarding packets to other nodes. Load distribution constitutes another important approach to the optimisation of active communication energy. Load distribution enables the maximisation of the network lifetime by facilitating the avoidance of over-utilised nodes when a route is in the process of being selected. Routing algorithms for mobile networks that attempt to optimise routes while at- tempting to retain a small message overhead and maximise the network lifetime has been put forward. However certain of these routing protocols have proved to have a negative impact on node and network lives by inadvertently over-utilising the energy resources of a small set of nodes in favour of others. The conservation of power and careful sharing of the cost of routing packets would ensure an increase in both node and network lifetimes. This thesis proposes simultaneously, by using an ant colony optimisation (ACO) approach, to optimise five power-aware metrics that do result in energy-efficient routes and also to maximise the MANET's lifetime while taking into consideration a realistic mobility model. By using ACO algorithms a set of optimal solutions - the Pareto-optimal set - is found. This thesis proposes five algorithms to solve the multi-objective problem in the routing domain. The first two algorithms, namely, the energy e±ciency for a mobile network using a multi-objective, ant colony optimisation, multi-pheromone (EEMACOMP) algorithm and the energy efficiency for a mobile network using a multi-objective, ant colony optimisation, multi-heuristic (EEMACOMH) algorithm are both adaptations of multi-objective, ant colony optimisation algorithms (MOACO) which are based on the ant colony system (ACS) algorithm. The new algorithms are constructive which means that in every iteration, every ant builds a complete solution. In order to guide the transition from one state to another, the algorithms use pheromone and heuristic information. The next two algorithms, namely, the energy efficiency for a mobile network using a multi-objective, MAX-MIN ant system optimisation, multi-pheromone (EEMMASMP) algorithm and the energy efficiency for a mobile network using a multi-objective, MAX- MIN ant system optimisation, multi-heuristic (EEMMASMH) algorithm, both solve the above multi-objective problem by using an adaptation of the MAX-MIN ant system optimisation algorithm. The last algorithm implemented, namely, the energy efficiency for a mobile network using a multi-objective, ant colony optimisation, multi-colony (EEMACOMC) algorithm uses a multiple colony ACO algorithm. From the experimental results the final conclusions may be summarised as follows:<ul><li> Ant colony, multi-objective optimisation algorithms are suitable for mobile ad hoc networks. These algorithms allow for high adaptation to frequent changes in the topology of the network. </li><li> All five algorithms yielded substantially better results than the non-dominated sorting genetic algorithm (NSGA-II) in terms of the quality of the solution. </li><li> All the results prove that the EEMACOMP outperforms the other four ACO algorithms as well as the NSGA-II algorithm in terms of the number of solutions, closeness to the true Pareto front and diversity. </li></ul> / Thesis (PhD)--University of Pretoria, 2010. / Computer Science / unrestricted

The works published by Giovanni Verga (1840-1922) between 1878 and 1889 exposed Italian culture to the most innovative European literary trend, French Naturalism, and marked a turning point in the landscape of Italian literature. While Verga’s stylistic choices are meant to create, in his own words, ‘the complete illusion of reality’ (having the author disappear from the text in order to make way for a supposedly unmediated representation), I argue that Verga’s Verist fiction ends up emphasizing precisely the ways in which people represent reality according to their own relative point of view. Since the narrative is given from the unreliable perspective of the characters, all the distortions inherent in every storytelling act become apparent. Their viewpoint is purposefully shown as being partial and informed by individual interests, feelings, and desires. These complex dynamics of representation, or misrepresentation, in Verga’s Verist production are at the heart of my enquiry. This critical focus allows me to reevaluate the traditional representation of Verism and Naturalism as backward-looking phenomena, firmly tied to a notion of art as a mirror up to nature. The present study is situated within a growing body of work (inaugurated by Luperini, Pellini, and Merola) that intends to re-frame Verga as having demonstrably paved the way for twentieth-century Modernism. The first chapter interrogates the way in which space is transfigured by characters in I Malavoglia (1881). By looking at how narratives of country vs city, past vs present are formed and shaped by the characters’ relative points of view, I argue that the novel should be read not simply as the account of the modernization of a rural village in post-unification Italy, but mainly as a study into how such oppositional narratives are formed and what aims they serve. The second chapter focuses on a specific character-type, the malevolent observer. I argue that this figure can be seen as a representation of the readers in the texts and that it is instrumental in exemplifying Verga’s skepticism toward the heuristic potential of literature. The third chapter examines the gap between reality and representation as articulated in Mastro-don Gesualdo (1889) by situating Verga in a completely new intellectual framework, that of elite theory as formulated by political theorist Gaetano Mosca (1858-1941) and sociologist Vilfredo Pareto (1848-1923). This move allows me to re-read what has become a commonplace of Verga criticism – the theatrical conception of politics in Mastro-don Gesualdo as a bitter commentary on trasformismo – as a much wider point on social history, human nature, and on the inherently slippery essence of language, on its built-in capacity to deceive and dissimulate.