The rise of the Swedish Democrats, as a political party in Sweden, has been surroundedby controversy both within and outside of the media. As such a polarizingtopic, the party has been the focus of negative and positive attention. On onehand it has been considered a racist and xenophobic party due to its policies onimmigrants. On the other, it has also been seen as a Solution to what has been consideredby some to be a constant problem in Sweden, for those same policies.These policies are motivated by what the party perceives as a threat to Swedishsociety. That is to say, immigrants are a threat to Sweden because of thechanges they impose on the Swedish identity.

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 main purpose of this essay was to understand and discuss the problems the Swedishmunicipalities have when missing the profession in cultural preservation area. I have madetwo case studies where competence has been present in one and absent in the other. FurtherI intend to find out what material the Swedish municipalities needs in their work with theconservation of built environment.The first case describes Vallentunas main intersection and the adjustments needed toseparate it from the local rail road. It identifies what the municipality deems importantsuch as sight lines and access to the old church area. The ability to illuminate these itemshad not been possible without the knowledge and early participation of an expert in thefield of cultural resource management.The second case revolves around an old croft in Österåker that was subject for a plannedresidential 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.

This master thesis investigates the possibilities of using GPS-information from trains to create a model of a railway system, register the routes of the the trains and predict how the trains will travel in the railway system.The thesis work was done at Icomera AB which is a company that specializes in internet connected vehicle Solutions.We describe how the GPS-information is sent from the trains in the form of samples and investigate limitations and possibilities with the available information. About three million samples from 83 SJ-trains were analysed and the samples were filtered with the intent of removing erroneous information. We here found that about 30 % of the samples from the trains were unreliable.A Solution for how the samples from the trains can be used to create a model of the railway system traveled by the trains is presented. We use a large set of historical samples and use cluster nodes and Hermite curves to generate a graph that represent the railway system with stations, nodes and the railway itself. A fully automatic Solution is not presented since it did not fit into the time frame of the thesis; instead we created a simple tool which can be used to manually finish the model of the railway system.Furthermore, we describe how the railway system and the samples from the train can be used to register the routes the trains travel.

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 main purpose of this project was to make a survey of the steam and electricity consumption at Akzo Nobel Functional Chemistry AB and give suggestions of how to minimize them. These three different areas were focused on. First to make a survey of all the most important consumers, second to find the electricity consumption of the air compressors and the amount of waste heat produced from them. The third area was to calculate a model of how much fresh water that is used during a cooling sequence in the water based heating/cooling system of the reactors and give a suggestion of a suitable reuse for this water.The main result is a total survey of the energy consumption in steam and electricity. The survey shows that the second largest group after drying is heating of ventilation which gives big potentials of reducing the total steam consumption if there is a way of being self supporting in ventilation heat.

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.

SCA is the largest private owned forest owner in Sweden, with an ownership of 2 million hectares of productive forestland. To manage the planning of such large areas and to fit the traditional organization structure of a Swedish forest company, the planning approach is subdivided into three stages; strategic, tactical and operational. The strategic part, based on a statistic sample of stands, returns a harvest level estimate which should then be implemented at actual sites in the tactical part. This procedure can lead to incompatible Solutions as the strategic Solution is not necessarily possible to translate into actual sites in the tactical plan. The geographic aspect is important in tactical planning due to the large costs for moving equipment and maintenance of a large number of forest roads.