## Abstract

Practical applications of scheduling, routing and other generic constrained optimization problems often involve an uncertainty in the values of the data presented in the problem data instances. On the contrary, most of the established algorithms for typical classes of well-studied problems in the field of constrained optimization assume that deterministic precise values of data would be known. Hence, any solution developed for a specific optimization problem with a given problem data instance would become non-optimal and/or infeasible when applied to another data instance with even slight perturbation. We argue the fallacy of using solutions developed based on the mean values of data for real life problems having stochastic data.

Original language | English |
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Title of host publication | Combinatorial Algorithms : 23rd International Workshop, IWOCA 2012, Krishnankoil, India, July 19-21, 2012, Revised Selected Papers |

Editors | S. Arumugam, W.F. Smyth |

Number of pages | 5 |

Publisher | Springer |

Publication date | 2012 |

Pages | 76-80 |

ISBN (Print) | 978-3-642-35925-5 |

DOIs | |

Publication status | Published - 2012 |

MoE publication type | A4 Article in conference proceedings |

Event | 23rd International Workshop on Combinatorial Algorithms, IWOCA 2012 - Tamil Nadu, India Duration: 19.07.2012 → 21.07.2012 |

### Publication series

Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 7643 LNCS |

ISSN (Print) | 0302-9743 |

ISSN (Electronic) | 1611-3349 |

## Keywords

- 113 Computer and information sciences