Fuzzy Optimization Using Direct Crisp and Fuzzy Interval Comparison

  • Pavel V. Sevastjanov
  • Paweł Róg
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 19)


In real optimization tasks, always there are two main groups of criteria: requirements of outcomes increasing or expenses decreasing and demands of uncertainty reduction, in other words, risk minimization. Therefore, it seems advisable to formulate optimization problem under conditions of uncertainty as, at least, two-objective on the basis of local criteria of benefits increasing or expenses reduction and risk minimization. Generally, risk may be treated as the uncertainty of result obtained. In a situation considered, the degree of risk (uncertainty) may be defined in natural way as width of final interval of target function at the point of obtained optimum. To solve the problem briefly described above, the technique of two-objective crisp and fuzzy interval comparison has been developed on the base of probability approach to interval comparison taking into account the relation of compared intervals widths. To illustrate the efficiency of method proposed, the simple example of minimization in the case of interval double-extreme discontinuous cost function of real argument is presented.


Fuzzy Number Local Criterion Multiobjective Programming Fuzzy Optimization Fuzzy Interval 
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 2003

Authors and Affiliations

  • Pavel V. Sevastjanov
    • 1
  • Paweł Róg
    • 1
  1. 1.Institute of Math. & Comp. Sci.Technical University of CzestochowaCzestochowaPoland

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