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: Palliative care is something that all people should have the right to be allowed to, to be able to enjoy the qualities of life, even when someone has been afflicted with illness that cannot be cured. How do the nurses in municipal home-care deal with and prepare themselves to perform a righteous task? Aim: The aim of this study is to illuminate nurses, comprehensions of palliative care within municipal home-care. Method: The method is a questionnaire to nurses. Results: The results did comply to law and regulations.

In a school for children from 6-9 years in a small town in the southeast of Sweden, is areading activity program in progress since 8 years. The original purpose of this program wasto enhance the student?s reading interest. All of the students read at least one book a week andthen they review the book in front of the class.The purpose of the present study was to examine vocabulary, word retrieving, narrative skillsand grammatical abilities in children in this school. The objectives were to investigate if thechosen language abilities in these children were different compared to normative data andearlier studies in children at comparable ages.

The business world of today is characterized by the fact that knowledge plays a far greater role than it did before in the companies? production. In many companies, the human resources constitute the main part of the total assets. It can for example be the employees? knowledge, competence or power of initiative.

AimThe aim of the study was to develop a method for the survey of play movement demands and temporal patterns in order to enable a descriptive study of the defensive players in American Football. The overall aim was to  improve the understanding of how American Football is played to create opportunities for enhancement of current or developing new training methods to better suit football.MethodFifty plays from a Division 3 college football game on video from 2005 was divided into sequences of action for one player each from the defensive line, linebackers and defensive backs and analyzed with the video analyzing software cSwing. Every players sequence of action was recorded in a spreadsheet and noted on a scaled football field where distances were measured and together with time stamps from cSwing velocity was calculated.ResultsUsing this method it was possible to describe the play movement demands and temporal patterns which was the main task of the study. The defensive end worked on an average 4.61 seconds per play, the distance was 12.4 meters and average speed 2.5 m×s-1. The linebacker worked on an average 4.35 s per play, 13.7 m and at a mean speed of 3.0 m×s-1.

Purpose: The purpose of this paper is to study how important brand belonging can be for sport clubs.Method: The method for the empirical research is based on qualitative interviews. The data then gets compared and connected with relevant brand and marketing theories.Findings: The paper finds out the perks and disadvantages the researched clubs gain from the strong brand names they hold, and further discussion for development based on theory is being made..

Purpose: The purpose of this work is to investigate teachers' professional attitude to homework as a method. The study will also provide answers to the purpose for which the homeworks are used in teaching and if the individual circumstances and needs are met by this method.Method: Qualitative research was conducted through interviews with four teachers from three different schools. In addition, published surveys were used in support of reasoning.Results: Neither the curriculum or the syllabus mentions homework. There are no directives for how much time should be dispensed with and the extent of a homework should be. In teacher training literature the homework is not discussed.

Around 85 percent of the total population in Sweden today lives in an urban environment. This means that the nature within the urban areas has come to play an important role for the human well being. At the broader picture, the nature within urban areas is profitable in many ways. It is therefore important for the municipalities around in Sweden to work for sustainability within the urban areas. Linköping adopted an environmental policy, in year 2001, from the delegate of the municipality.

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 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.