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  • 401.
    Ölvander, Johan
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Maskinkonstruktion.
    Design of Fluid Power Systems Using a Multi-Objective Genetic Algorithm2004Ingår i: Applications of Multi-Objective Evolutionary Algorithms / [ed] Carlos A. Coello Coello, Gary B. Lamont, Singapore: World Scientific , 2004, s. -761Kapitel i bok, del av antologi (Övrigt vetenskapligt)
    Abstract [en]

    This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding as well as the use of MOEAs, the aim being to find good solutions for high-dimensional real-world design applications. The book contains a large collection of MOEA applications from many researchers, and thus provides the practitioner with detailed algorithmic direction to achieve good results in their selected problem domain.

  • 402.
    Ölvander, Johan
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Maskinkonstruktion.
    Robustness considerations in multi-objective optimal design2005Ingår i: Journal of engineering design (Print), ISSN 0954-4828, E-ISSN 1466-1837, Vol. 16, nr 5, s. 511-523Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In real-world engineering design problems we have to search for solutions that simultaneously optimize a wide range of different criteria. Furthermore, the optimal solutions also have to be robust. Therefore, this paper presents a method where a multi-objective genetic algorithm is combined with response surface methods in order to assess the robustness of the identified optimal solutions. The design example is two different concepts of hydraulic actuation systems, which have been modelled in a simulation environment to which an optimization algorithm has been coupled. The outcome from the optimization is a set of Pareto optimal solutions that elucidate the trade-off between energy consumption and control error for each system. Based on these Pareto fronts, promising regions could be identified for each concept. In these regions, sensitivity analyses are performed and thus it can be determined how different design parameters affect the system at different optimal solutions.

  • 403.
    Ölvander, Johan
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Maskinkonstruktion.
    Sensitivity Analysis in Multi-objective Evolutionary Design, in Recent Advances in Simulated Evolution and Learning2004Ingår i: Recent Advances in Simulated Evolution and Learning / [ed] K. C. Tan, Singapore: World Scientific series on Advances in Natural Computation , 2004, 2, s. -832Kapitel i bok, del av antologi (Övrigt vetenskapligt)
    Abstract [en]

          Inspired by the Darwinian framework of evolution through natural selection and adaptation, the field of evolutionary computation has been growing very rapidly, and is today involved in many diverse application areas. This book covers the latest advances in the theories, algorithms, and applications of simulated evolution and learning techniques. It provides insights into different evolutionary computation techniques and their applications in domains such as scheduling, control and power, robotics, signal processing, and bioinformatics. The book will be of significant value to all postgraduates, research scientists and practitioners dealing with evolutionary computation or complex real-world problems

  • 404.
    Ölvander, Johan
    et al.
    Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Maskinkonstruktion. Linköpings universitet, Tekniska högskolan.
    Feng, X.
    ABB Corporate Research, Västerås, Sweden.
    Holmgren, B.
    ABB Corporate Research, Västerås, Sweden.
    Optimal kinematics design of an industrial robot family in 2008 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC 2008, vol 1, issue PART B, pp 777-7872009Ingår i: ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference: Volume 1: 34th Design Automation Conference, Parts A and B, The American Society of Mechanical Engineers (ASME) , 2009, Vol. 1, nr PART B, s. 777-787Konferensbidrag (Refereegranskat)
    Abstract [en]

    Product family design is a well recognized method to address the demands of mass customization. A potential drawback of product families is that the performance of individual members are reduced due to the constraints added by the common platform, i.e. parts and components need to be shared by other family members. This paper presents a formal mathematical framework where the product family design problem is stated as an optimization problem and where optimization is used to find an optimal product family. The object of study is kinematics design of a family of industrial robots. The robot is a serial manipulator where different robots share arms from a common platform. The objective is to show the trade-off between the size of the common platform and the kinematics performance of the robot.

  • 405.
    Ölvander, Johan
    et al.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Maskinkonstruktion.
    Krus, Petter
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för konstruktions- och produktionsteknik, Maskinkonstruktion.
    A multi-objective optimization approach to aircraft preliminary design2004Ingår i: SAE Transactions Journal of Aerospace, s. 454-460Artikel i tidskrift (Refereegranskat)
  • 406.
    Ölvander, Johan
    et al.
    Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Maskinkonstruktion. Linköpings universitet, Tekniska högskolan.
    Lundén, Björn
    Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Maskinkonstruktion. Linköpings universitet, Tekniska högskolan.
    Gavel , Hampus
    Saab Aerosystems.
    A computerized optimization framework for the morphological matrix applied to aircraft conceptual design2009Ingår i: Computer-Aided Design, ISSN 0010-4485, E-ISSN 1879-2685, Vol. 41, nr 3, s. 187-196Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents a formal mathematical framework for the use of the morphological matrix in a computerized conceptual design framework. Within the presented framework, the matrix is quantified so that each solution principle is associated with a set of characteristics such as weight, cost, performance, etc. Selection of individual solutions is modeled with decision variables and an optimization problem is formulated. The applications are the conceptual design of subsystems for an Unmanned Aerial Vehicle and an aircraft fuel transfer system. Both the system models and the mathematical framework are implemented in MS Excel.

  • 407.
    Ölvander, Johan
    et al.
    Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Maskinkonstruktion. Linköpings universitet, Tekniska högskolan.
    Tarkian, Mehdi
    Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Maskinkonstruktion. Linköpings universitet, Tekniska högskolan.
    Feng, Xiaolong
    Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Maskinkonstruktion. Linköpings universitet, Tekniska högskolan.
    Multi-objective Optimization of a family of Industrial Robots2011Ingår i: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing / [ed] Wang L., Ng A. H.C., Deb K., Springer Verlag , 2011, s. 189-217Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    With the increasing complexity and dynamism in today’s product design and manufacturing, more optimal, robust and practical approaches and systems are needed to support product design and manufacturing activities. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing presents a focused collection of quality chapters on state-of-the-art research efforts in multi-objective evolutionary optimisation, as well as their practical applications to integrated product design and manufacturing. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing consists of two major sections. The first presents a broad-based review of the key areas of research in multi-objective evolutionary optimisation. The second gives in-depth treatments of selected methodologies and systems in intelligent design and integrated manufacturing. Recent developments and innovations in multi-objective evolutionary optimisation make Multi-objective Evolutionary Optimisation for Product Design and Manufacturing a useful text for a broad readership, from academic researchers to practicing engineers.

6789 401 - 407 av 407
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