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 thesis presents an optimally designed kinematic structure for a new 6-DOF haptic devicebased on TAU configuration. The configuration of the TAU-2 proposed by Suleman Khan andKjell Andersson [1] was modified and its mobility was verified by using Grübler criterion tohave a 6 DOF. Analytical kinematic models for the inverse and forward kinematics weredeveloped for the haptic TAU configuration to determine a set of optimal design parameters.Kinematic performance indices such as volume of the workspace, kinematic isotropy and payload index, were defined based on the singular values of the Jacobian matrix. The Jacobianmatrix was scaled to homogenize the physical units. The Jacobian matrix dependent on theposition and orientation of the end-effector gives local isotropy and pay load index, so globaldesign indices were defined, which represent the performance of the mechanism in the wholeworkspace.

This paper discusses an osteological- and archeological analysis of a cairn from the Bronze Age on Gotland. The osteological material consists of both burnt and and unburnt bones from both human and animal. The objective of this paper is to shed light on the individuals who were buried in the cairn. It is also to generate information about continuity in its use and patterns of distribution of the bones and grave-goods in the cairn. The osteological analysis show that a minimum of five human individuals is present in the osteological material.

Abstract Title: Ethanol for Scania?s future ? A scenario based analysis Authors: Anna Hansson and Julia Persson Tutors: Annette Cerne ? Department of Business Administration, Lund University Jonas Holmborn ? Head of Advanced Combustion, Engine Development, Scania Lennart Thörnqvist ? Department of Energy Sciences, Faculty of Engineering, Lund University Problem: Oil-based products are the dominating fuels in the transport sector but alternative fuels are currently challenging the world-wide dominance. The large number of alternative fuels that are under development at present makes the future fuel-market impossible to predict. Scania?s ethanol project is associated with a number of uncertainty factors that are beyond the company?s control.

Modelica is a multi-domain and equation-based modeling language. Modelica is based on object-oriented principles and non-causal modeling. The language is constructed to facilitate reuse and decompose models. The models and the modellibrary can modified to design a new nonlinear components.Object-oriented modeling is an excellent way to analyze and study large complex heterogeneous physical systems. The object-oriented modeling approach build on reusing and decomposition of models and non-causal modeling.Modeling physical systems often leads to a DAE system with index 2 or 3.

Modern missiles must meet higher and higher demands. They should be autonomous, have long range and still have a big effect on the target. To maximize effect on target some missiles not only minimize miss distance, but also try to hit with a certain angle; often perpendicular to the surface of the target. In this thesis a method to guide the missile in the terminal phase of its mission where both point of impact as angle of impact are specified. The method consist of two parts.

New technologies and new consumer behaviors are having a large impact on mediacompanies. The biggest change is in the behavior of the younger demographic whereold platforms like television are abandoned for new online platforms. In this newworld, media companies and organizations need new tools and business models tostay competitive. One such tool is Design Thinking, a term used to describe a cognitivedesign-specific set of activities used during a design process. It has been popularizedin commercial areas and there the term is used to describe an applicable workflowused to promote the skills required to use Design Thinking.

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.