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 thesis is to investigate and analyze existing law concerning joint owner-ship in agriculture and forestry businesses. Joint ownership often arises through a succes-sion of ownership, therefore we will go through the most useful methods.Even if the owners of agriculture and forestry businesses are getting older, the numbers of succession of ownerships are still low. A succession of ownership is important to plan and its time is demanding. Often it takes three to five years for the completion of a succession of ownership. Therefore, owners must start their planning in time and think about what is to come of their business.

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.

GE Healthcare wants to investigate whether additive manufacturing would be an alternative method in their workshops in the Umea? plant. Additive manufacturing is called 3D printing in everyday language and manufactures details by building them up layer by layer in an automated machine. The purpose of this work is therefore to investigate how mature additive manufacturing methods are and how they could be used at GE.The work has been divided into three parts. The first section investigates how additive manufacturing would work in the production workshop at GE.

This thesis studies the negative impact that control signal saturation may have on a controlled system. Different methods that are used to compensate for this problem are also studied and evaluated. Both sensitivity to disturbances and the effect the method has on the systems'ability to follow a reference signal will be examined. Stability will be discussed, but no conclusions whether the systems are stabilized or not can be drawn. Control signal saturation will lead to a slower behavior in general.

At present day there are several different methods for measuring of paved surfaces.The most common methods today are measuring with a total station, the GlobalNavigation Satellite System (GNSS) and terrestrial laser scanning (TLS). Recently thedevelopment of unmanned aerial vehicles, known as drones, has increasedexponentially and today there are several ways of using drones for measuring surfacesby photographing and laser scanning.This thesis contains a comparison between the methods terrestrial laser scanning(TLS), and unmanned aerial vehicle photogrammetry (UAV). The measurements havebeen applied on two different test surfaces, one of asphalt and one of gravel. Thepurpose of the comparison is to investigate whether the airborne photogrammetry isequivalent accurate in its height levels as the terrestrial laser scanning. For thecomparison to be more extensive, these two methods have not only been comparedin precision but also in the areas of ease of use and economy.The precision was analyzed by comparing the height levels in randomly placed controlpoints on the test surfaces.

The aim of the study was to investigate the students´ attitudes towards mathematics, their knowledge in the subject area they find the least interesting and whether laborative/practical working methods could awaken their interest and curiosity. During our work, we have looked into previous studies regarding girls´ and boys´ attitude and performance in mathematics. We handed out surveys to students in grade 9 at a School with many people from other cultures and nationalities in Malmö in order to find the answers to our questions. The result showed that most of the students thought that the subject area "scaling" was the least interesting. The implemented action program was a laborative/practical task within the "scaling" area.

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.

This study was conducted in the Master program at The Music Pedagogical Center (MPC) at The Royal College of Music in Stockholm. Korta musikresor (Short Music Journeys) is the Swedish term used for a receptive method of music therapy adapted from the tradition of The Bonny Method of Guided Imagery and Music (BMGIM) and the theory and practice of Expressive Arts Therapy. The KMR method uses carefully selected short pieces of music, lasting between 2 and 5 minutes, to work on various psychological problems and life- crises. The music session is conducted in a slightly altered state of consciousness with a clear focus being established beforehand in a verbal dialogue with the psychotherapist. There is also the possibility of using artwork to process and explore the imagery after the music listening.

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.