Multiple Objective Path Optimization for Time Dependent Objective Functions

  • Michael M. Kostreva
  • Laura Lancaster
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 12)


The study of time dependent, non-monotone increasing objective functions is interesting for several applications of multiple objective path optimization. In this paper an algorithm which finds the set of non-dominated paths is derived and shown to converge. This algorithm does not reduce to dynamic programming, even for constant cost functions.


Cost Function Dynamic Programming Start Node Vector Cost Origin Node 
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 2002

Authors and Affiliations

  • Michael M. Kostreva
    • 1
  • Laura Lancaster
    • 1
  1. 1.Department of Mathematical SciencesClemson UniversityClemsonUSA

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