Search for dissertations about: "Evolutionary multi-objective optimization"

Showing result 1 - 5 of 6 swedish dissertations containing the words Evolutionary multi-objective optimization.

  1. 1. Metamodel based multi-objective optimization

    University dissertation from Jönköping : Jönköping University, School of Engineering

    Author : Kaveh Amouzgar; Högskolan i Jönköping.; [2015]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Multi-objective optimization; strength Pareto evolutionary algorithm; SPEA2; metamodel; surrogate model; response surface; radial basis functions; RBF;

    Abstract : As a result of the increase in accessibility of computational resources and the increase in the power of the computers during the last two decades, designers are able to create computer models to simulate the behavior of a complex products. To address global competitiveness, companies are forced to optimize their designs and products. READ MORE

  2. 2. Multi-objective optimization of railway bogie suspension damping

    University dissertation from Chalmers University of Technology

    Author : Albin Johnsson; Chalmers tekniska högskola.; Chalmers University of Technology.; [2011]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Optimeringslära; systemteori; Optimization; systems theory; Farkostteknik; Vehicle engineering; Fastkroppsmekanik; Solid mechanics; Övrig teknisk mekanik; Other engineering mechanics; Multi-objective optimization; Railway vehicle dynamics; Bogie suspension design; Pareto optimized bogie primary and secondary suspensions damping;

    Abstract : In this thesis multi-objective optimization is used to find Pareto fronts showing the set of optimized damping parameters of primary and secondary bogie suspensions. Special interests are put on requirements to enhance safety and comfort of a railway vehicle. READ MORE

  3. 3. Dynamic Resampling for Preference-based Evolutionary Multi-objective Optimization of Stochastic Systems Improving the efficiency of time-constrained optimization

    University dissertation from Skövde : Högskolan i Skövde

    Author : Florian Siegmund; Högskolan i Skövde.; Högskolan i Skövde.; [2016]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Evolutionary multi-objective optimization; simulation-based optimization; guided search; preference-based optimization; reference point; decision support; noise; stochastic systems; dynamic resampling; budget allocation; sequential sampling; hybrid; ranking and selection; Naturvetenskap; Natural sciences; Teknik; Technology;

    Abstract : In preference-based Evolutionary Multi-objective Optimization (EMO), the decision maker is looking for a diverse, but locally focused non-dominated front in a preferred area of the objective space, as close as possible to the true Pareto-front. Since solutions found outside the area of interest are considered less important or even irrelevant, the optimization can focus its efforts on the preferred area and find the solutions that the decision maker is looking for more quickly, i. READ MORE

  4. 4. District heating system analysis and challenges within the urban transformation of Kiruna

    University dissertation from Luleå : Luleå University of Technology

    Author : Mattias Vesterlund; Luleå tekniska universitet.; [2017]
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; District heating; analysis; optimization; design; heat production; Energy Engineering; Energiteknik;

    Abstract : There is currently an ongoing urban transformation in a small Swedish town named Kiruna, it is located in the very north of Sweden well above the Arctic Circle in a sub-arctic climate. Large part of the town will be relocated due to the ground deformation that is caused by the progressing iron ore mining activity and it is affecting all infrastructures of the town. READ MORE

  5. 5. Using Genetic Algorithms for Large Scale Optimizationof Assignment, Planning and Rescheduling Problems

    University dissertation from KTH Royal Institute of Technology

    Author : Irfan Younas; KTH.; [2014]
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; SRA - ICT; SRA - Informations- och kommunikationsteknik;

    Abstract : There has always been a need to solve real-life large-scale problems, suchas efficiently allocating limited resources, and other complex and conflicting situations related to combinatorial optimization genre. A class of combinato- rial optimization problems is NP-hard and, among many well-known, several of them are assignment, planning and rescheduling problems. READ MORE