Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-14555
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Main Title: Scheduling under Uncertainty: Optimizing Against a Randomizing Adversary
Author(s): Möhring, Rolf H.
Type: Research Paper
URI: https://depositonce.tu-berlin.de/handle/11303/15782
http://dx.doi.org/10.14279/depositonce-14555
License: http://rightsstatements.org/vocab/InC/1.0/
Abstract: Deterministic models for project scheduling and control suffer from the fact that they assume complete information and neglect random influences that occur during project execution. A typical consequence is the underestimation of the expected project duration and cost frequently observed in practice. To cope with these phenomena, we consider scheduling models in which processing times are random but precedence and resource constraints are fixed. Scheduling is done by policies which consist of an online process of decisions that are based on the observed past and the a priori knowledge of the distribution of processing times. We give an informal survey on different classes of policies and show that suitable combinatorial properties of such policies give insight into optimality, computational methods, and their approximation behavior. In particular, we present recent constant-factor approximation algorithms for simple policies in machine scheduling that are based on a suitable polyhedral relaxation of the performance space of policies.
Subject(s): uncertainty
scheduling
online algorithm
project planning
Issue Date: 2000
Date Available: 17-Dec-2021
Language Code: en
DDC Class: 510 Mathematik
MSC 2000: 90B36 Scheduling theory, stochastic
90B35 Scheduling theory, deterministic
68M20 Performance evaluation; queueing; scheduling
Series: Preprint-Reihe des Instituts für Mathematik, Technische Universität Berlin
Series Number: 2000, 681
ISSN: 2197-8085
TU Affiliation(s): Fak. 2 Mathematik und Naturwissenschaften » Inst. Mathematik
Appears in Collections:Technische Universität Berlin » Publications

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