Sampling Method for the Flow Shop with Uncertain Parameters

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10244)

Abstract

In the classic approach for optimization problems modelling well defined parameters are assumed. However, in real life problems we find ourself very often in a situation where parameters are not defined precisely. This may have many sources like inaccurate measurement, inability to establishing precise values, randomness, inconsistent information or subjectivity.

In this paper we propose a sampling method for solving optimization problems with uncertain parameters modeled by random variables. Moreover, by applying confidence intervals theory, the execution time has been significantly reduced. We will also show an application of the method for the flowshop problem with deadlines and parameters modeled by random variables with the normal distribution.

Keywords

Flowshop with deadlines Uncertain parameters Tabu search Normal distribution 

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Copyright information

© IFIP International Federation for Information Processing 2017

Authors and Affiliations

  1. 1.Institute of Computer ScienceUniversity of WrocławWrocławPoland

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