Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-14443
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Main Title: Decision Support and Optimization in Shutdown and Turnaround Scheduling
Author(s): Megow, Nicole
Möhring, Rolf H.
Schulz, Jens
Type: Research Paper
URI: https://depositonce.tu-berlin.de/handle/11303/15670
http://dx.doi.org/10.14279/depositonce-14443
License: http://rightsstatements.org/vocab/InC/1.0/
Abstract: This paper concerns the highly complex task of scheduling large-scale maintenance activities during a plants shutdown or turnaround. We model it as a discrete time-cost tradeoff problem with capacity constraints and individual working shifts for different resource types with a cost function regarding a balanced resource consumption. We introduce and model the problem, give an overview on the large variety of related optimization problems, and propose a framework for supporting managers decisions in the planning process of such an event. Our key component is an optimization algorithm complemented with a risk analysis of solutions. We implemented a two-phase solution method in which we first provide an approximation of the tradeoff between project duration and cost as well as a stochastic evaluation of the risk for meeting the makespan. In a second, detailed planning phase, we solve the actual scheduling optimization problem for a chosen deadline heuristically and compute a detailed schedule that we complement by evaluating upper bounds for the two risk measures expected tardiness and the probability of meeting the deadline. We present experimental results showing that our methods can handle large real-world instances within seconds and yield a leveled resource consumption. For smaller instances a comparison with solutions of a time-consuming mixed integer program prove the high quality of the solutions that our fast heuristic produces.
Subject(s): scheduling
malleable jobs
time-cost tradeoff
project management
stochastic analysis
optimization
resource leveling
Issue Date: 2009
Date Available: 17-Dec-2021
Language Code: en
DDC Class: 510 Mathematik
Series: Preprint-Reihe des Instituts für Mathematik, Technische Universität Berlin
Series Number: 2009, 09
ISSN: 2197-8085
TU Affiliation(s): Fak. 2 Mathematik und Naturwissenschaften » Inst. Mathematik
Appears in Collections:Technische Universität Berlin » Publications

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