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 aim of this research was to examine how the relationship between consultants and their customers can increase the value for the customer and to see how consultants can act to gain closer relationships with the customers. An empirical study has been performed through case studies with a consultant and six customers to the consultant. The theoretical areas for the analysis are customer value and relationship development between seller and buyer. Our conclusions of the research were that values for the customers are increases with closer relationships. The increased value lays in lesser uncertainty when repurchasing.

This text answers the questions how do we define what a campus is, how the concept of the campus came to exist and how it is used today, and how the Blekinge Institute of Technology (BTH) campus can be designed according to site conditions and the conclusions drawn from case studies at Chalmers University of Technology and Karlstad University. The purpose of the case studies is to gain insight into their campuses advantages and disadvantages. This finally results in an interpretation of how the Blekinge Institute of Technology campus can be planned. A campus is the area of land on which a college or university and its surrounding buildings resides on. Campus as a concept meant a field at first, it later evolved at American universities due to their design of college campuses.

Difficult calvings and stillborn calves are costly for the producer and lowering these frequencies can decrease the costs for the dairy operation. Each calving in the herd is registered by the farmer and stored in a central database. The information is used to monitor the level of calving-difficulties and stillborn calves in the herd and nationally. Monitoring of these registrations is important to detect possible changes. Breeding-value prediction for calving traits is based on the calving information in the database.

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 thesis aim to explain which part sound and music possess as a branding tool. We consider this to be of relevance since there is very limited reseach conducted on the subject. To fulfill the purpose of this thesis we have focused on three main issues. Our ambition is to describe this subject from a marketing perspective with the brand in focus.

The purpose of this thesis is to define and theorise willingness-to-support as a possible measurement of corporate reputation. The knowledge production in this thesis is done through reasoning with companies to gain a deeper understanding of the social world and the respondents? view of their reality. Grounded theory is used as an inspiration for conducting the research. A qualitative method is used in the form of semi-structured interviews with six companies in three different business sectors.

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.

Background: How a young woman approaches an abortion and how she handles its emotional impact is influenced by many factors. Mixed emotions about terminating a pregnancy are common to women of all backgrounds and circumstances. Aim: To illuminate young women´s experiences of abortions. Method: The study wasbased on literature from online databases and printed materials and involved the analysis of ten articles and one thesis. Result: Women contemplating abortion experience mixed emotions before, during, and after an abortion.

The idea behind this project came from a feed study executed two years during the lambing season. Both years wool loss was experienced. Low temperature in combination with shearing was believed to cause the wool loss the first year, while protein deficiency was believed to be the cause the second year. In the literature many causes of wool loss are described; mechanical wear, telogen effluvium, bacterial dermatitis, external parasites, wool break, scrapie, genetic causes and nutritional deficiencies are some examples. The aim of this thesis was to study causes for wool loss and how common wool loss is in Swedish sheep herds.

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.