Publications
207 results found
Parpas P, Rustem B, 2009, Convergence analysis of a global optimization algorithm using stochastic differential equations, Journal of Global Optimization, Vol: 45, Pages: 95-110
Miri T, Tsoukalas A, Bakalis S, et al., 2008, Global optimization of process conditions in batch thermal sterilization of food, JOURNAL OF FOOD ENGINEERING, Vol: 87, Pages: 485-494, ISSN: 0260-8774
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- Citations: 26
Osorio MA, Gulpinar N, Rustem B, 2008, A mixed integer programming model for multistage mean-variance post-tax optimization, EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, Vol: 185, Pages: 451-480, ISSN: 0377-2217
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- Citations: 5
Faisca NP, Kouramas KI, Saraiva PM, et al., 2008, A multi-parametric programming approach for constrained dynamic programming problems, OPTIMIZATION LETTERS, Vol: 2, Pages: 267-280, ISSN: 1862-4472
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- Citations: 20
Osorio MA, Gulpmar N, Rustem B, 2008, A general framework for multistage mean-variance post-tax optimization, 12th Biennial Latin-Ibero-American Conference on Operations Research, Publisher: SPRINGER, Pages: 3-23, ISSN: 0254-5330
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- Citations: 4
Pistikopoulos EN, Faísca NP, Saraiva PM, et al., 2008, Bilevel Programming Framework for Enterprise-Wide Process Networks Under Uncertainty, Encyclopedia of Optimization, Publisher: Springer US, Pages: 248-255, ISBN: 9780387747583
Parpas P, Rustem B, 2008, Maximum Entropy and Game Theory, Encyclopedia of Optimization, Publisher: Springer US, Pages: 1999-2004, ISBN: 9780387747583
Parpas P, Rustem B, 2008, Global Optimization Algorithms for Financial Planning Problems, Encyclopedia of Optimization, Publisher: Springer US, Pages: 1277-1282, ISBN: 9780387747583
Parpas P, Rustem B, 2008, Laplace Method and Applications to Optimization Problems, Encyclopedia of Optimization, Publisher: Springer US, Pages: 1818-1822, ISBN: 9780387747583
Parpas P, Rustem B, 2008, Duality Gaps in Nonconvex Optimization, Encyclopedia of Optimization, Publisher: Springer US, Pages: 802-805, ISBN: 9780387747583
Parpas P, Rustem B, 2008, Decomposition Algorithms for the Solution of Multistage Mean-Variance Optimization Problems, Encyclopedia of Optimization, Publisher: Springer US, Pages: 619-627, ISBN: 9780387747583
Kuhn D, Parpas P, Rustem B, 2008, Bound-based decision rules in multistage stochastic programming, Vol: 44, Pages: 134-150
We study bounding approximations for a multistage stochastic program with expected value constraints. Two simpler approximate stochastic programs, which provide upper and lower bounds on the original problem, are obtained by replacing the original stochastic data process by finitely supported approximate processes. We model the original and approximate processes as dependent random vectors on a joint probability space. This probabilistic coupling allows us to transform the optimal solution of the upper bounding problem to a near-optimal decision rule for the original problem. Unlike the scenario tree based solutions of the bounding problems, the resulting decision rule is implementable in all decision stages, i.e., there is no need for dynamic reoptimization during the planning period. Our approach is illustrated with a mean-risk portfolio optimization model.
Rustem B, Zakovi S, Parpas P, 2008, Convergence of an interior point algorithm for continuous minimax, Journal of Optimization Theory and Applications, Vol: 136, Pages: 87-103
Parpas P, Rustem B, 2008, A pricing mechanism for resource management in grid computing, Computational Economics, Vol: 4, Pages: 381-295
Miri T, Bakalis S, Rustem B, et al., 2008, Global and local optimization of food quality in batch thermal processes, FOODSIM'2008: 5TH INTERNATIONAL CONFERENCE ON SIMULATION AND MODELLING IN THE FOOD AND BIO-INDUSTRY, Pages: 17-+
Rustem B, Zakovi, Parpas P, 2008, An interior point algorithm for continuous minimax: implementation and computation, Optimization Methods and Software, Vol: 23, Pages: 911-928-911-928
Gulpinar N, Rustem B, 2007, Worst-case robust decisions for multi-period mean-variance portfolio optimization, EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, Vol: 183, Pages: 981-1000, ISSN: 0377-2217
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- Citations: 77
Ẑaković S, Wieland V, Rustem B, 2007, Stochastic optimization and worst-case analysis in monetary policy design
In this paper we compare expected loss minimization to worst-case or minimax analysis in the design of simple Taylor-style rules for monetary policy. To this end we use a small model estimated for the euro area by Orphanides and Wieland (2000). We find that rules optimized under a minimax objective in the presence of general parameter and shock uncertainty do not imply extreme policy activism. Such rules also tend to obey the Brainard principle, which implies that policy responsiveness declines with increasing uncertainty about policy effectiveness. We find that rules derived by means of minimax analysis are effective insurance policies limiting maximum loss over ranges of parameter values to be set by the policy maker. In practice, we propose to set these ranges with an eye towards the cost of such insurance cover in terms of the implied increase in expected inflation variability. © Springer Science+Business Media, Inc. 2006.
Žaković S, Wieland V, Rustem B, 2007, Stochastic Optimization and Worst-Case Analysis in Monetary Policy Design, Computational Economics, Vol: 30, Pages: 329-347
Kuhn D, Parpas P, Rustem B, 2007, Threshold accepting approach to improve bound-based approximations for portfolio optimization
Gulpinar N, Harder U, Harrison P, et al., 2007, Mean-variance performance optimization of response time in a tandem router network with batch arrivals, Publisher: Springer Verlag, Pages: 203-216, ISSN: 1386-7857
The end-to-end performance of a simple wireless router network with batch arrivals is optimized in an M/G/1 queue-based, analytical model. The optimization minimizes both the mean and variance of the transmission delay (or æresponse timeÆ), subject to an upper limit on the rate of losses and finite capacity queueing and recovery buffers. Losses may be due to either full buffers or corrupted data. The queueing model is also extended to higher order moments beyond the mean and variance of the response time. The trade-off between mean and variance of response time is assessed and the optimal ratio of arrival-buffer size to recovery-buffer size is determined, which is a critical quantity, affecting both loss rate and transmission time. Graphs illustrate performance in the near-optimal region of the critical parameters. Losses at a full buffer are inferred by a time-out whereas corrupted data is detected immediately on receipt of a packet at a router, causing a N-ACK to be sent upstream. Recovery buffers hold successfully transmitted packets so that on receiving a N-ACK, the packet, if present, can be retransmitted, avoiding an expensive resend from source. The impact of the retransmission probability is investigated similarly: too high a value leads to congestion and so higher response times, too low and packets are lost forever.
Gulpinar N, Rustem B, 2007, Robust optimal decisions with imprecise forecasts, COMPUTATIONAL STATISTICS & DATA ANALYSIS, Vol: 51, Pages: 3595-3611, ISSN: 0167-9473
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- Citations: 11
Guelpinar N, Rustem B, Zakovic S, 2007, Stochastic Optimization and Worst-case Decisions, 5th International Conference on Cooperative Control and Optimization, Publisher: SPRINGER-VERLAG BERLIN, Pages: 317-338, ISSN: 0075-8442
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- Citations: 2
Parpas P, Rustem B, 2007, Computational assessment of nested Benders and augmented Lagrangian decomposition for mean-variance multistage stochastic problems, INFORMS Journal on Computing, Vol: 19, Pages: 239-147
Rustem B, Gulpinar N, 2007, Worst-case Optimal Robust Decisions for Multi-period Portfolio Optimization, European Journal of Operational Research
Faisca NP, Kouramas KI, Saraiva PM, et al., 2007, Robust dynamic programming via multi-parametric programming, 17th European Symposium on Computer Aided Process Engineering (ESCAPE-17), Publisher: ELSEVIER SCIENCE BV, Pages: 811-816, ISSN: 1570-7946
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- Citations: 1
Rustem B, Dua V, Saraiva P, et al., 2007, Parametric global optimisation for bilevel programming, Journal of Global Optimization
Faísca NP, Dua V, Saraiva PM, et al., 2006, A parametric programming approach to supply chains problems, CHISA 2006 - 17th International Congress of Chemical and Process Engineering
In this work, a parametric programming based approach is proposed to the hierarchical plant selection problem. Based on recently proposed multi-parametric programming algorithms (Dua et al., 2002; Dua and Pistikopoulos, 2000), multi-level programming problems can be solved without disassembling the multi-level nature of them, since the rational reaction sets can be computed in advance and thereby the leader can choose the global optimum. Moreover, since the rational reaction set is computed through the Basic Sensitivity Theorem (Fiacco, 1983), the behaviour of the follower will be given by an affine function of the leader's variables. Consequently, in the upper level no extra numerical complexity is introduced. The advantage of this technique is that the parametric nature of the leader's problem is preserved and allows for possible comparisons between global optima. The underlying mathematical theory and a illustrating example are provided.
Gulpinar N, Harrison P, Rustem B, 2006, Worst-case Analysis of Router Networks with Rival Queueing Models, 21st Int. Symp. on Computer and Information Sciences, Istanbul, Turkey, Publisher: Springer-Verlag, LNCS
Gulpinar N, Harrison P, Rustem B, et al., 2006, Optimization of a Tandem Router Network Using a Fluid Model, 9th ACM/IEEE International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM 2006), Publisher: ACM
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