Portfolio selection is an example of decision making under conditions of uncertainty. In the face of an unknown future, fund managers make complex financial choices based on the investors perceptions and preferences towards risk and return. Since the seminal work of Markowitz, many studies have been published using his mean-variance (MV) model as a basis. These mathematical models of investor attitudes and asset return dynamics aid in the portfolio selection process. In this thesis we extend the MV model to include the cardinality constraints which limit the number of assets held in the portfolio and bounds on the proportion of an asset held (if any is held). We present our formulation based on the Markowitz MV model for rebalancing an existing portfolio subject to both fixed and variable transaction cost (the fee associated with trading). We determine and demonstrate the differences that arise in the shape of the trading portfolio and efficient frontiers when subject to non-cardinality and cardinality constrained transaction cost models. We apply our flexible heuristic algorithms of genetic algorithm, tabu search and simulated annealing to both the cardinality constrained and transaction cost models to solve problems using data from seven real world market indices. We show that by incorporating optimization into the generation of valid portfolios leads to good quality solutions in acceptable computational time. We illustrate this on problems from literature as well as on our own larger data sets.

In this thesis we have presented a mathematical model of a scheduling problem which arises in the Brewing Industry. We have implemented two different types of global optimization algorithms to find the global minimum of the problem. Several instances of the scheduling problem are considered and the results thereof are presented. The results show that significant savings can be made if the global optimization techniques are used in brewery Industry.

Heat Recovery Steam Generator (HRSG) systems in conjunction with a primary gas turbine and a secondary steam turbine can provide advanced modern power generation with high thermal efficiency at low cost. To achieve such low cost efficiencies, near optimal settings of parameters of the HRSG must be employed. Unfortunately, current approaches to obtaining such parameter settings are very limited. The published literature associated with the Tabu Search (TS) metaheuristic has shown conclusively that it is a powerful methodology for the solution of very challenging large practical combinatorial optimization problems. This report documents a hybrid TS-direct pattern search (TS-DPS) approach and applied to the thermoeconomic optimization of a three pressure level HRSG system. To the best of our knowledge, this algorithm is the first to be developed that is capable of successfully solving a practical HRSG system. A requirement of the TS-DPS technique was the creation of a robust simulation module to evaluate the associated extremely complex 19 variable objective function. The simulation module was specially constructed to allow the evaluation of infeasible solutions, a highly preferable capability for methods like TS-DPS. The direct pattern search context is explicitly embodied within the TS neighborhoods permitting different neighborhood structures to be tested and compared. Advanced TS is used to control the associated continuum discretization with minimal memory requirements. Our computational studies show that TS is a very effective method for solving this HRSG optimization problem. / text

The object of Master Thesis is the creation and research optimization of blank realization procedures. Four main parts comprise the thesis: analysis of the problem, theoretical solutions, research and outcomes, conclusions and recommendations. Optimization methods, their advantages and limitations have been analyzed in the first part. The most appropriate optimization method for problem solving was selected. Designed optimization methods have been presented in the theoretical solutions part: exhaustive search, tabu search and a new one, presented by the author. A program was created for comparison of these methods. In the third part of the thesis outcomes of the research are presented. Designed methods were tested and compared by their routes length, process time, computations duration and other parameters. Conclusions of the thesis and recommendations for implementation of analyzed procedures have been presented in the part of conclusions. Literature in Lithuanian, English was used in preparing the thesis. There are 19 tables and 29 pictures in the thesis.

It is a well-known fact that project activities are subject to considerable uncertainty, which may lead to multiple schedule disruptions during project execution. As a result, the random nature of activity durations has been the subject of numerous research efforts since the introduction of the initial PERT. A common problem which arises in project management is the fact that the planned schedule is often disrupted by several uncontrollable factors like weather conditions, other environmental factors, additional time that might be required for rework and correction of detected defects. As a result, project managers are often unable to meet the promised completion dates. It is therefore vital to take into account such possible disruptions and their potential negative consequences at the project schedule design stage. Hence, the ability of the pre-schedule to absorb disruptions may be very important in such settings. At this point two new criteria are used in modern scheduling literature: &quot / robustness&quot / and &quot / stability&quot / . In this thesis, we propose several stability measures. These measures are embedded in a tabu search algorithm to generate stable schedules in a multi resource environment subject to random disruptions.

No description available.

No description available.

No description available.

This work concerns new borders, heuristics, algoritms and mathematic models of pallet loading problem (PLP). We try to describe these computational methods and find out if we can use them in real. We maximalize number of boxes placed on rectangular pallets in a particular warehouse by using chosen heuristics. Every box has a rectangular form with the same lenght and width and is fully placed on the pallet. We can rotate with the box by 90% degree until it is fixed as we want and its side lies parallelly with side of the pallet. All instances are setted in model (X, Y, a, b), where X is lenght, Y width of the pallet, a lenght and b width of the box.

Made available in DSpace on 2017-07-21T14:19:39Z (GMT). No. of bitstreams: 1 Robson Fernando Duda.pdf: 3342961 bytes, checksum: 3f61d3a8f1dcfb461c6860c82d3f54db (MD5) Previous issue date: 2014-02-28 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / This paper presents a solution to the routing problem of vehicles with homogeneous fleet. To do so, heuristic and metaheuristic based algorithms applied towards the development of a decision support system, with georeferenced interface were developed. The algorithms had as base heuristic methods built in two phases, besides a metaheuristic. The interface layer used as visualization component is based in cartographic data that indicates the location of the points to be assisted and the paths that connects them, forming a road system represented using the Google Maps® API. The algorithms were validated using instances from the literature, presenting satisfactory results regarding optimization based in the methods that were used, showing that it is possible the usage of the developed system in the distribution of agricultural products. / Este trabalho apresenta uma solução para o problema de roteamento de veículos com frotas homogêneas. Para tanto, foram desenvolvidos algoritmos baseados em heurísticas e meta-heurísticas aplicadas ao desenvolvimento de um sistema de apoio a decisão, com interface georreferenciada. Os algoritmos tiveram como base métodos heurísticos construtivos e em duas fases, além de uma meta-heurística. A camada de interface utilizada como componente de visualização é baseada em dados cartográficos que indicam a localização dos pontos a serem atendidos e as vias que os interligam, formando a malha viária que é representada utilizando a API do Google Maps®. Os algoritmos foram validados utilizando instâncias da literatura, apresentando resultados satisfatórios em relação a otimização baseada nos métodos utilizados, mostrando ser possível a utilização do sistema desenvolvido para a distribuição de produtos agrícolas.