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35
Optimal linear precoding strategies for wideband noncooperative systems based on game theory – Part II: Algorithms
 IEEE Trans. Signal Process
, 2008
"... In this twoparts paper we propose a decentralized strategy, based on a gametheoretic formulation, to find out the optimal precoding/multiplexing matrices for a multipointtomultipoint communication system composed of a set of wideband links sharing the same physical resources, i.e., time and band ..."
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Cited by 29 (3 self)
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In this twoparts paper we propose a decentralized strategy, based on a gametheoretic formulation, to find out the optimal precoding/multiplexing matrices for a multipointtomultipoint communication system composed of a set of wideband links sharing the same physical resources, i.e., time and bandwidth. We assume, as optimality criterion, the achievement of a Nash equilibrium and consider two alternative optimization problems: 1) the competitive maximization of mutual information on each link, given constraints on the transmit power and on the spectral mask imposed by the radio spectrum regulatory bodies; and 2) the competitive maximization of the transmission rate, using finite order constellations, under the same constraints as above, plus a constraint on the average error probability. In Part I of the paper, we start by showing that the solution set of both noncooperative games is always nonempty and contains only pure strategies. Then, we prove that the optimal precoding/multiplexing scheme for both games leads to a channel diagonalizing structure, so that both matrixvalued problems can be recast in a simpler unified vector power control game, with no performance penalty. Thus, we study this simpler game and derive sufficient conditions ensuring the uniqueness of the Nash equilibrium. Interestingly, although derived under stronger constraints,
Generation of yieldaware pareto surfaces for hierarchical circuit design space exploration
 In DAC
, 2006
"... Pareto surfaces in the performance space determine the range of feasible performance values for a circuit topology in a given technology. We present a nondominated sorting based global optimization algorithm to generate the nominal pareto front efficiently using a simulatorinaloop approach. The ..."
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Cited by 9 (0 self)
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Pareto surfaces in the performance space determine the range of feasible performance values for a circuit topology in a given technology. We present a nondominated sorting based global optimization algorithm to generate the nominal pareto front efficiently using a simulatorinaloop approach. The solutions on this pareto front combined with efficient Monte Carlo approximation ideas are then used to compute the yieldaware pareto fronts. We show experimental results for both the nominal and yieldaware pareto fronts for power and phase noise for a voltage controlled oscillator (VCO) circuit. The presented methodology computes yieldaware pareto fronts in approximately 56 times the time required for a single circuit synthesis run and is thus practically efficient. We also show applications of yieldaware paretos to find the optimal VCO circuit to meet the system level specifications of a phase locked loop.
Novel quantitative tools for engineering analysis of hepatocyte cultures in bioartificial liver systems
 Biotechnology and Bioengineering
, 2005
"... are perhaps among the most promising technologies for the treatment of liver failure, but significant technical challenges remain in order to develop systems with sufficient processing capacity and of manageable size. One key limitation is that during BAL operation, when the device is exposed to pla ..."
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Cited by 6 (2 self)
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are perhaps among the most promising technologies for the treatment of liver failure, but significant technical challenges remain in order to develop systems with sufficient processing capacity and of manageable size. One key limitation is that during BAL operation, when the device is exposed to plasma from the patient, hepatocytes are prone to accumulate intracellular lipids and exhibit poor liverspecific functions. Based on hepatic intermediary metabolism, we have utilized mathematical programming techniques to optimize the biochemical environment of hepatocyte cultures towards the desired effect of increased albumin and urea synthesis. To investigate the feasible range of optimal hepatic function, we have obtained a Pareto optimal set of solutions corresponding to liverspecific functions of urea and albumin secretion in the metabolic framework using multiobjective optimization. The importance of amino acids in the supplementation and the criticality of the metabolic pathways have been investigated using logicbased programming techniques. Since the metabolite measurements are bound to be patient specific, and hence subject to variability, uncertainty has to be integrated with system analysis to improve the prediction of hepatic function. We have used the concept of two stage stochastic programming to obtain robust solutions by considering extracellular variability. The proposed analysis represents a new systematic approach to analyze behavior of hepatocyte cultures and optimize different operating parameters for an extracorporeal device based on realtime conditions.
SimX: Parallel system software for interactive multiexperiment computational studies
 In Parallel & Distributed Processing Symposium (IPDPS
, 2006
"... Advances in highperformance computing have led to the broad use of computational studies in everyday engineering and scientific applications. A single study may require thousands of computational experiments, each corresponding to individual runs of simulation software with different parameter sett ..."
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Cited by 5 (3 self)
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Advances in highperformance computing have led to the broad use of computational studies in everyday engineering and scientific applications. A single study may require thousands of computational experiments, each corresponding to individual runs of simulation software with different parameter settings; in complex studies, the pattern of parameter changes is complex and may have to be adjusted by the user based on partial simulation results. Unfortunately, existing tools have limited highlevel support for managing large ensembles of simultaneous computational experiments. In this paper, we present a system architecture for interactive computational studies targeting two goals. The first is to provide a framework for highlevel user interaction with computational studies, rather than individual experiments; the second is to maximize the size of the studies that can be performed at close to interactive rates. We describe a prototype implementation of the system and demonstrate performance improvements obtained using our approach for a simple model problem. 1
Generate pareto optimal solutions of scheduling problems using normal boundary intersection technique
 Computers and Chemical Engineering
"... The problem of shortterm scheduling under uncertainty is addressed in this paper through a multiobjective optimization framework that incorporates economic expectation, robustness, and flexibility in terms of demand satisfaction. In order to be able to identify Pareto optimal solutions, a new appro ..."
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Cited by 4 (2 self)
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The problem of shortterm scheduling under uncertainty is addressed in this paper through a multiobjective optimization framework that incorporates economic expectation, robustness, and flexibility in terms of demand satisfaction. In order to be able to identify Pareto optimal solutions, a new approach is applied which is based on normal boundary intersection (NBI) technique. The main advantage of this technique is that it avoids the selection of arbitrary parameters and generates a set of evenly distributed set of points independent of the scales of the objectives. Utilizing this idea, alternative schedules are generated that represent tradeoff between the various objectives in the face of uncertainty. The approach is illustrated through three case studies and the special characteristics of the scheduling problems are discussed.
Constructing Approximations to the Efficient Set of Convex Quadratic Multiobjective Problems
, 2002
"... In multicriteria optimization, several objective functions have to be minimized simultaneously. For this kind of problem, no single solution can adequately represent the whole set of optimal points. We propose a new efficient method for approximating the solution set of a convex quadratic multiobjec ..."
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Cited by 4 (0 self)
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In multicriteria optimization, several objective functions have to be minimized simultaneously. For this kind of problem, no single solution can adequately represent the whole set of optimal points. We propose a new efficient method for approximating the solution set of a convex quadratic multiobjective programming problem. The method is based on a warmstart interior point algorithm for which we derive complexity results, thereby extending previous results by Yildirim & Wright. Numerical results on bicriteria problems from power plant optimization and portfolio optimization show that the method is an order of magnitude faster than standard methods applied to the problems considered.
EFFECTIVE GENERATION OF PARETO SETS USING GENETIC PROGRAMMING
, 2001
"... Many designers concede that there is typically more than one measure of performance for an artifact. Often, a large system is decomposed into smaller subsystems each having its own set of objectives, constraints, and parameters. The performance of the final design is a function of the performances o ..."
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Cited by 2 (0 self)
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Many designers concede that there is typically more than one measure of performance for an artifact. Often, a large system is decomposed into smaller subsystems each having its own set of objectives, constraints, and parameters. The performance of the final design is a function of the performances of the individual subsystems. It then becomes necessary to consider the tradeoffs that occur in a multiobjective design problem. The copmplete
DESIGN OF TIMEMODULATED LINEAR ARRAYS WITH A MULTIOBJECTIVE OPTIMIZATION AP PROACH
"... Abstract—This article proposes a Multiobjective Optimization (MO) framework for the design of timemodulated linear antenna arrays with ultra low maximum Side Lobe Level (SLL), maximum Side Band Level (SBL) and main lobe Beam Width between the First Nulls (BWFN). In contrast to the existing optimiz ..."
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Cited by 2 (1 self)
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Abstract—This article proposes a Multiobjective Optimization (MO) framework for the design of timemodulated linear antenna arrays with ultra low maximum Side Lobe Level (SLL), maximum Side Band Level (SBL) and main lobe Beam Width between the First Nulls (BWFN). In contrast to the existing optimizationbased methods that attempt to minimize a weighted sum of SLL, SBL, and BWFN, we treat these as three distinct objectives that are to be achieved simultaneously and use one of the best known MultiObjective Evolutionary Algorithms (MOEAs) of current interest called MOEA/DDE (Decomposition based MOEA with Differential Evolution operator) to determine the best compromise among these three objectives. Unlike the singleobjective approaches, the MO approach provides greater flexibility in the design by yielding a set of equivalent final solutions from which the user can choose one that attains a suitable tradeoff margin as per requirements. We compared timemodulated antenna structures with other methods for linear array synthesis such as the excitation method and the phaseposition synthesis method on the basis of the approximated Pareto Fronts (PFs) yielded by MOEA/DDE and the best compromise solutions determined from the Pareto optimal set with a fuzzy membershipfunction based method. The final results obtained with MOEA/DDE were compared with the results achieved by two stateoftheart single objective optimization algorithms and five other MO algorithms. Our simulation studies on three instantiations of the design problem reflect the superiority of the MOEA/DDE based design of timemodulated linear arrays.