Search for dissertations about: "multi-objective optimization"

Showing result 1 - 5 of 52 swedish dissertations containing the words multi-objective optimization.

  1. 1. Metamodel based multi-objective optimization

    Author : Kaveh Amouzgar; Peter Hansbo; Niclas Strömberg; Kent Salomonsson; Sunith Bandaru; Högskolan i Jönköping; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; NATURVETENSKAP; NATURAL SCIENCES; 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. Learning from Multi-Objective Optimization of Production Systems : A method for analyzing solution sets from multi-objective optimization

    Author : Catarina Dudas; Henrik Boström; Amos H.C. Ng; Johan Ölvander; Stockholms universitet; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; Data mining; Post-optimization analysis; Production system analysis; Computer and Systems Sciences; data- och systemvetenskap;

    Abstract : The process of multi-objective optimization involves finding optimal solutions to several objective functions. However, these are typically in conflict with each other in many real-world problems, such as production system design. READ MORE

  3. 3. Robust Multi-objective Optimization of Rare Earth Element Chromatography

    Author : Hans-Kristian Knutson; Institutionen för kemiteknik; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Chromatography; Rare earth elements; Modeling; Multi-objective optimization; Robust optimization; Chromatography; Rare earth elements; Modeling; Multi-objective optimization; Robust optimization;

    Abstract : Rare earth elements comprise the metallic elements known as lanthanides as well as scandium and yttrium. They are extensively used in modern technological industries and are considered as strategic commodities in many countries. READ MORE

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

    Author : Albin Johnsson; Chalmers University of Technology; []
    Keywords : NATURVETENSKAP; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; ENGINEERING AND TECHNOLOGY; ENGINEERING AND TECHNOLOGY; Railway vehicle dynamics; Bogie suspension design; Multi-objective optimization; 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

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

    Author : Florian Siegmund; Kalyanmoy Deb; Amos H.C. Ng; Sanaz Mostaghim; Högskolan i Skövde; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; NATURVETENSKAP; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; 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; Natural sciences; Naturvetenskap; Technology; Teknik; Production and Automation Engineering; Produktion och automatiseringsteknik;

    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