Many-Objective Optimization: An Engineering Design Perspective

  • Peter J. Fleming
  • Robin C. Purshouse
  • Robert J. Lygoe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3410)


Evolutionary multicriteria optimization has traditionally concentrated on problems comprising 2 or 3 objectives. While engineering design problems can often be conveniently formulated as multiobjective optimization problems, these often comprise a relatively large number of objectives. Such problems pose new challenges for algorithm design, visualisation and implementation. Each of these three topics is addressed. Progressive articulation of design preferences is demonstrated to assist in reducing the region of interest for the search and, thereby, simplified the problem. Parallel coordinates have proved a useful tool for visualising many objectives in a two-dimensional graph and the computational grid and wireless Personal Digital Assistants offer technological solutions to implementation difficulties arising in complex system design.


Pareto Front Multiobjective Optimization Problem Multiobjective Evolutionary Algorithm Brake Torque True Pareto Front 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Peter J. Fleming
    • 1
  • Robin C. Purshouse
    • 2
  • Robert J. Lygoe
    • 3
  1. 1.Department of Automatic Control and Systems EngineeringUniversity of SheffieldSheffieldUK
  2. 2.PA Consulting GroupLondonUK
  3. 3.Powertrain Applications Product DevelopmentFord Motor Company Ltd 

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