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Applications of Semidefinite Optimization in Stochastic Project Scheduling

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dc.contributor.author Bertsimas, Dimitris J.
dc.contributor.author Natarajan, Karthik
dc.contributor.author Teo, Chung Piaw
dc.date.accessioned 2003-12-23T01:59:12Z
dc.date.available 2003-12-23T01:59:12Z
dc.date.issued 2002-01
dc.identifier.uri http://hdl.handle.net/1721.1/3994
dc.description.abstract We propose a new method, based on semidefinite optimization, to find tight upper bounds on the expected project completion time and expected project tardiness in a stochastic project scheduling environment, when only limited information in the form of first and second (joint) moments of the durations of individual activities in the project is available. Our computational experiments suggest that the bounds provided by the new method are stronger and often significant compared to the bounds found by alternative methods. en
dc.description.sponsorship Singapore-MIT Alliance (SMA) en
dc.format.extent 124719 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.relation.ispartofseries High Performance Computation for Engineered Systems (HPCES);
dc.subject project scheduling en
dc.subject problem of moments en
dc.subject semidefinite programming en
dc.subject co-positivity en
dc.subject tardiness en
dc.title Applications of Semidefinite Optimization in Stochastic Project Scheduling en
dc.type Article en


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