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.
Khalid Saeed; Władysław Homenda; Rituparna Chaki. 16th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Jun 2017, Bialystok, Poland. Springer International Publishing, Lecture Notes in Computer Science, LNCS-10244, pp.580-591, 2017, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-59105-6_50〉
https://hal.inria.fr/hal-01656238
Contributeur : Hal Ifip
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Soumis le : mardi 5 décembre 2017 - 14:58:22
Dernière modification le : mercredi 6 décembre 2017 - 01:20:59
Paweł Rajba, Mieczysław Wodecki. Sampling Method for the Flow Shop with Uncertain Parameters. Khalid Saeed; Władysław Homenda; Rituparna Chaki. 16th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Jun 2017, Bialystok, Poland. Springer International Publishing, Lecture Notes in Computer Science, LNCS-10244, pp.580-591, 2017, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-59105-6_50〉. 〈hal-01656238〉
