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.

Larsson, Linda (2012) Erfarenhetslärande i skolan: - Belyst genom en kvalitativ fallstudie av en studieresa. Examensarbete på avancerad nivå i pedagogik. Akademin för utbildning och ekonomi. Lärarprogrammet på högskolan i Gävle.Syftet med denna kvalitativa studie är att undersöka erfarenhetsbaserat lärande i skolan. För att göra det har jag valt en skola som har infört en tradition att deras niondeklassare får arbeta fram pengar och åka på en studieresa till Auschwitz i Polen.

Due to better nutrition, veterinary and overall care, pet dogs? lifespan has increased. With more old dogs we see more health problems associated with age, among those cognitive decline, leading to deficits in learning and memory, disorientation, anxiety and other altered behaviors. Cognitive decline can have severe negative impacts on the life of both dog and owner, when the dog for example forgets being housetrained or starts being awake at night. Two pet food manufacturers have developed food with specific ingredients in order to improve cognitive functions or delay the onset of cognitive impairment. Hill?s Pet Nutrition has developed a dog food with supplements of a broad spectrum of antioxidants and mitochondrial nutrients, aiming to diminish oxidative damage in the brain, thereby maintaining brain function and improving learning ability.

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.

Vi, Linda Runvall och Satu Parantainen, har gjort vårt examensarbete för företaget Leine & Linde i Strängnäs. De tillverkar pulsgivare som används inom industrin. Examensarbetet bestod av att göra om en befintlig manual och skriva guidelines (riktlinjer) till Leine & Lindes personal.Under vårt examensarbete har vi använt oss av våra kunskaper inom informationsdesign. Rune Pettersson, professor i informationsdesign vid Mälardalens högskola, beskriver ämnet informationsdesign såhär:?In order to satisfy the information needs of the intended receivers information design comprises analysis, planning, presentation and understanding of a message- its content, language and form.

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.

Linda Åkerstedt (2010). Kunskap finns överallt. En studie om användandet av hjälpmedel i skolan idag. Malmö: Lärarutbildningen: Malmö Högskola. Examensarbetet handlar om vilka hjälpmedel som är förekommande i skolan idag. Syftet med arbetet är att undersöka vilka hjälpmedel som används i undervisningen, samt ta reda på hur de används. Om det finns situationer då användandet av hjälpmedel är accepterat respektive icke accepterat studeras också.

Titel: Kunskap ? nyckeln till framgång? Seminariedatum: 2011-01-12Högskola: Mälardalens Högskola VästeråsInstitution: Akademin för hållbar samhälls- och teknikutvecklingÄmne/kurs: Kandidatuppsats i företagsekonomi ? FÖA 300Författare: Linda Lycken (780131) och Rafael Vega Trujillo (870711)Handledare: Sara Melén Nyckelord: Innovation, kunskap, knowledge managementSyfte: Uppsatsens syfte är att få en djupare förståelse för den kunskap som finns på ASSA samt att se hur kunskap påverkar utvecklingen av innovationer.Metod: Kvalitativ och deduktiv metod. En fallstudie har genomförts genom 2 semistrukturerade intervjuer på ASSA. Teori: Teorikapitlet baseras på vetenskapliga artiklar och böcker om innovation, kunskap och  knowledge management.Empiri: Empirikapitlet består av intervjuer med två anställda på ASSA, Perla Bovin som är designansvarig samt projektansvarig Jonas Herrmann. Dessutom har ASSAs webbplats och årsredovisning från 2009 använts.Slutsats: Det går att identifiera synlig och osynlig kunskap på ASSA.