The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

This thesis examines underpricing and the long run performance of IPO firms on the Swedish equity market during 1994-2010. We further investigate whether any correlation exist between underpricing and post-IPO performance during 36 months. We use a sample of 80 IPO firms. To examine the aftermarket performance we compare total return of each firm with a matching industry index. In order to strengthen our analysis, we run a second test, comparing actual return for each firm with expected return, adjusted for firm specific risk.

During the last few years, there has been a lot of debate regarding the price ofelectricity on the Swedish market. According to a recent survey from Sifo, anon-bias governmental institute for consumer research and testing, the priceof electricity is what worries Swedish households the most. An investigationof the eciency of the Nordic power grids inuence on the Swedish spotprice is therefore both relevant and valuable. Three quarters of all electricityproduced in the Nordic region is traded at the Nord Pool Spot power market.This survey examines how much of the variation of the swedish spot pricecan be descried by the variation of the nordic system price and how much iscaused because of ineciencies in the power grid. Primarily, linear regressionwith adjustments for endogeneity and heteroskedasticity has been used in orderto analyze data obtained mainly from Nord Pool Spot and Vattenfall AB.The results show that the variation of the system price can account for all butabout 40% of the variation in the Swedish spot price.

Introduction: Each year 1200-1300 patients are diagnosed with head neck cancer. Treatment that involves radiotherapy can cause severe side effects for example trismus that affects quality of life.Purpose: To study health-related quality of life in patients who have undergone radiation treatment for head and neck cancer and participated in a intervention group who received training intended to prevent trismus or in a control group who received standard treatment.Method: This is a prospective study in which data is collected from 66 patients participating in a randomized study aiming to evaluate a training program to prevent trismus. Thirty three participated in the intervention group and thirty three in the control group. Both patient groups assessed health related quality of life (HRQOL) with EORTC QLQ C30 and QLQ-H&N35, at start and end of the radiation treatment, and at 3 and 6-months after completing radiation treatment.Results: There is no difference between the intervention and control groups regarding symptoms, functional status and global health, except for intake of nutritional supplements.  For both groups almost all scales measuring HRQOL deteriorated under the radiation treatment. However, 3 and 6 months after end of radiotherapy HRQOL had improved and had returned to the baseline values.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

Objectives. The aim of the present study was to examine the relationship between the personality variables Multidimensional Health Locus of Control (MHLC), Negativ affect and Social inhibition (the D-personality), and health behavior and attitudes toward keep-fit measures.Methods. The participants in this study were 170 embloyees at a regional social insurance office in a midsize town in the south of Sweden. Scales concerning health behavior and attitudes toward keep-fit measures were constructed and the participants completed these scales as well as those of MHLC and D-personality.Results. Participants with strong beliefs that other people, such as doctors or family-members, are responsible for their health, showed a more positive attitude as to keep-fit measures than those with a belief that health is controlled by themselves.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

The purpose of this study was to investigate produced laser data from the new national height model's airborne laser scanning in Sweden, what quality it has and whether it can be used for forest management planning. From airborne laser scanning one can obtain information on forest variables such as tree species, height, diameter and basal area. Norra skogsägarna is the principal employer of this project and they wanted know to the quality of the laser data which needs to cope with their standards. If the laser data the quality required it can replace some of the operations performed by field planners. To examine the quality of the produced laser data a control tax assessment has been performed in 30 forest departments. This was done in an objective manner.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.