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Non-Linear Programming Solvers for Decision Analysis
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Institutionen för informationsteknologi och medier. (FSCN - Fibre Science and Communication Network)
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Institutionen för informationsteknologi och medier.ORCID-id: 0000-0002-0665-1889
2004 (engelsk)Inngår i: Operations Research Proceedings 2003: Selected Papers of the International Conference on Operations Research (OR 2003) Heidelberg, September 3-5, 2003, Springer , 2004, s. 475-Konferansepaper, Publicerat paper (Annet vitenskapelig)
Abstract [en]

Several methods have been developed over a number of years for solving decision problems when vague and numerically imprecise information prevails. However, the DELTA method and similar methods give rise to particular bilinear programming problems that are time consuming to solve in a real-time environment. This paper presents a set of benchmark tests for non-linear programming solvers for solving this special type of problems. With two existing linear programming based algorithms, it also investigates the performance of linear programming solvers for special decision situations in decision support systems.

sted, utgiver, år, opplag, sider
Springer , 2004. s. 475-
Emneord [en]
decision analysis, nonlinear programming, linear programming, quadratic programming
HSV kategori
Identifikatorer
URN: urn:nbn:se:miun:diva-1708Lokal ID: 355ISBN: 3-540-21445-3 (tryckt)OAI: oai:DiVA.org:miun-1708DiVA, id: diva2:26740
Tilgjengelig fra: 2008-09-30 Laget: 2008-09-30 Sist oppdatert: 2018-01-12bibliografisk kontrollert
Inngår i avhandling
1. Bilinear optimization in computational decision analysis
Åpne denne publikasjonen i ny fane eller vindu >>Bilinear optimization in computational decision analysis
2005 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

In real-life decision analysis, significant recognition has been given to theunrealistic expectation of numerically precise information. Many modernapproaches attempting to handle imprecision have focused more on representationand less on evaluation. The DELTA method, as one of the fewleading approaches, challenges this issue by its evaluation framework thatcan accommodate both precision and imprecision. However, computationally,DELTA and similar approaches may incur time-consuming calculationsdue to the introduction of imprecise information concerning probability andutility. In general, those problems are bounded non-convex bilinear optimizationprograms with disjoint linear constraints, which cannot be solvedeffectively by any existing general-purpose global optimization technique.This thesis presents two enhanced cutting plane algorithms for solvingbounded disjoint bilinear programs arising in computational decision analysis.Each algorithm consists of a local phase designed to determine a localoptimizer from an approximate solution, and a global phase designed to systematicallyexplore the feasible region, subset by subset. These two phasesare switched automatically during the global search procedure. The basicframework builds upon previously developed efficient cutting plane methods.By embedding the lower bounding technique in a branch and bound procedure,the improvement of their performances seems encouraging in the lightof computational experience. Even though the motivation to develop thesealgorithms stems from computational decision analysis, the idea can also beextended to the development of optimization approaches for handling generalbounded disjoint bilinear programs, especially for larger sized ones.

sted, utgiver, år, opplag, sider
Sundsvall: Mittuniversitetet, 2005
Serie
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 2
HSV kategori
Identifikatorer
urn:nbn:se:miun:diva-8856 (URN)
Disputas
2005-05-27, O102, Åkroken, Sundsvall, 13:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2009-05-06 Laget: 2009-05-06 Sist oppdatert: 2018-01-13bibliografisk kontrollert

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