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13
Empirical Investigation of the Benefits of Partial Lamarckianism
, 1997
"... Genetic algorithms (GAs) are very efficient at exploring the entire search space; however, they are relatively poor at finding the precise local optimal solution in the region in which the algorithm converges. Hybrid genetic algorithms are the combination of improvement procedures, which are good at ..."
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Cited by 21 (2 self)
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Genetic algorithms (GAs) are very efficient at exploring the entire search space; however, they are relatively poor at finding the precise local optimal solution in the region in which the algorithm converges. Hybrid genetic algorithms are the combination of improvement procedures, which are good at finding local optima, and genetic algorithms. There are two basic strategies for using hybrid GAs. In the first, Lamarckian learning, the genetic representation is updated to match the solution found by the improvement procedure. In the second, Baldwinian learning, improvement procedures are used to change the fitness landscape, but the solution that is found is not encoded back into the genetic string. This paper examines the issue of using partial Lamarckianism, i.e., the updating of the genetic representation for only a percentage of the individuals, as compared to pure Lamarckian and pure Baldwinian learning in hybrid GAs. Multiple instances of five bounded nonlinear problems, the locat...
Optimizing Amplifier Placements in a Multiwavelength Optical LAN/MAN: The Unequally Powered Wavelengths Case
 IEEE/OSA Journal of Lightwave Technology
, 1998
"... Abstract—Wavelength division multiplexing (WDM) provides the ability to utilize the enormous bandwidth offered by optical networks, using today’s electronics. WDMbased optical networks employing passivestar couplers have been proposed for deployment in local and metropolitan areas. Optical amplifi ..."
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Cited by 15 (3 self)
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Abstract—Wavelength division multiplexing (WDM) provides the ability to utilize the enormous bandwidth offered by optical networks, using today’s electronics. WDMbased optical networks employing passivestar couplers have been proposed for deployment in local and metropolitan areas. Optical amplification is often required in such networks to compensate for the signal attenuation along the fiber links and the splitting and coupling losses in the network. However, an optical amplifier has constraints on the maximum gain and the maximum output power it can supply; thus optical amplifier placement becomes a challenging problem. A simplifying assumption for analytical tractability requires that all wavelengths, present at a particular point in a fiber, be at the same power level, viz. the equally poweredwavelengths case. However, previous studies did not minimize the total number of amplifiers while achieving power equalization. In this paper, we formulate the minimization of amplifiers with power equalization as a mixed integer linear program (MILP) that can be solved by a linear program solver. Illustrative examples on sample networks are presented, which demonstrate the characteristics and the advantages of our optimal amplifier placement algorithm. Index Terms — Amplifier placement, LAN/MAN, linear programming, optical network, optimization, passive star, power
3D Stereo Reconstruction of Human Faces driven by Differential Constraints
, 1999
"... Conventional stereo algorithms often fail in accurately reconstructing a 3D object because the image data do not provide enough information about the geometry of the object. We propose a way to incorporate a priori information in a reconstruction process from a sequence of calibrated face images. A ..."
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Cited by 12 (0 self)
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Conventional stereo algorithms often fail in accurately reconstructing a 3D object because the image data do not provide enough information about the geometry of the object. We propose a way to incorporate a priori information in a reconstruction process from a sequence of calibrated face images. A 3D mesh modeling the face is iteratively deformed in order to minimize an energy function. Differential information extracted from the object shape is used to generate an adaptive mesh. We also propose to explicitly incorporate a priori constraints related to the differential properties of the surface where the image information cannot yield an accurate shape recovery.
PowerDelay Optimizations in Gate Sizing
, 2000
"... The problem of powerdelay tradeoffs in transistor sizing is examined using a nonlinear optimization formulation. Both the dynamic and the shortcircuit power are considered, and a new modeling technique is used to calculate the shortcircuit power. The notion of transition density is used, with an ..."
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Cited by 9 (0 self)
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The problem of powerdelay tradeoffs in transistor sizing is examined using a nonlinear optimization formulation. Both the dynamic and the shortcircuit power are considered, and a new modeling technique is used to calculate the shortcircuit power. The notion of transition density is used, with an enhancement that considers the effect of gate delays on the transition density. When the shortcircuit power is neglected, the minimum power circuit is identical to the minimum area circuit. However, under our more realistic models, our experimental results on several circuits show that the minimum power circuit is not necessarily the same as the minimum area circuit.
Modeling paradigms applied to the analysis of European air quality
 EJOR
, 1999
"... The paper presents an overview of various modeling paradigms applicable to the analysis of complex decisionmaking problems that can be represented by large nonlinear models. Such paradigms are illustrated by their application to the analysis of a model that helps to identify and analyze various cos ..."
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Cited by 6 (3 self)
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The paper presents an overview of various modeling paradigms applicable to the analysis of complex decisionmaking problems that can be represented by large nonlinear models. Such paradigms are illustrated by their application to the analysis of a model that helps to identify and analyze various costeffective policy options aimed at improving European air quality. Also presented is the application of this model to support intergovernmental negotiations.
3D face modeling from stereo and differential
 constraints”, International Conference on Pattern Recognition
, 1998
"... This paper proposes a way to incorporate a priori information in a 3D stereo reconstruction process from a pair of calibrated face images. In our framework, a 3D mesh modeling the surface is iteratively deformed in order to minimize an energy function in a snakelike process. Differential informatio ..."
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Cited by 6 (0 self)
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This paper proposes a way to incorporate a priori information in a 3D stereo reconstruction process from a pair of calibrated face images. In our framework, a 3D mesh modeling the surface is iteratively deformed in order to minimize an energy function in a snakelike process. Differential information about the object shape is used to generate an anisotropic mesh that can both fulfill the compacity and the accuracy requirements. Moreover, in areas where the stereo information is not reliable enough to accurately recover the surface shape, because of inappropriate texture or bad lighting conditions, we propose to incorporate some geometric constraints related to the differential properties of the surface. These constraints can be intuitive or can refer to some predefined geometric properties of the object to be reconstructed. They can be applied to scalar fields, such as curvature values, or structural features, such as crest lines, governing their location, number, or spatial organization. We demonstrate our approach using faces.
A Concave Link Elimination (CLE) Procedure and Lower Bound for Concave Topology, Capacity and Flow Assignment Network Design Problems
, 1997
"... We examine the Concave Topology Capacity and Flow Assignment (TCFA) problem. Only two algorithms in the literature are appropriate for solving TCFA problems with concave link cost functions: Kleinrock and Gerla's Concave Branch Elimination (CBE) procedure, [26][20], and a greedy link eliminatio ..."
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Cited by 2 (0 self)
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We examine the Concave Topology Capacity and Flow Assignment (TCFA) problem. Only two algorithms in the literature are appropriate for solving TCFA problems with concave link cost functions: Kleinrock and Gerla's Concave Branch Elimination (CBE) procedure, [26][20], and a greedy link elimination procedure developed by Gersht [21]. However, neither works well in practice. The CBE procedure does not perform well in the context of strongly concave link cost functions. While Gersht's algorithm performs well, its processing requirements are such that it is applicable for small network design problems only. We present a Concave Link Elimination (CLE) procedure, based on Gersht's greedy link elimination procedure. Our algorithm is shown to perform at least as well as Gersht's procedure and to be significantly faster than both the CBE and Gersht procedures. In addition, we formulate a lower bounding problem which we solve using a continuous branchandbound procedure to assess the quality of t...
LARTTE: A PosynomialBased Lagrangian Relaxation Tuning Tool for Fast and Effective GateSizing and Multiple Vt Assignment
"... Abstract — In this paper, we propose a novel method for fast and effective gatesizing and multiple Vt assignment using Lagrangian Relaxation (LR) and posynomial modeling. Our algorithm optimizes a circuit’s delay and power consumption subject to slew rate constraints, and can readily take process v ..."
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Abstract — In this paper, we propose a novel method for fast and effective gatesizing and multiple Vt assignment using Lagrangian Relaxation (LR) and posynomial modeling. Our algorithm optimizes a circuit’s delay and power consumption subject to slew rate constraints, and can readily take process variation into account. We first use SPICE to generate accurate delay and power models in posynomial form for standard cells, then formulate a largescale, convex optimization problem based on these models. Finally, we perform LR to solve for the globallyoptimal 1 set of transistor sizes and Vts (with discretization) for each gate. Our key contribution is that we show for the first time that using posynomial models, LRbased circuit tuning can be carried out in a ”generalized ” or nonGaussSeidel manner for improved accuracy. Experimental results show that our implemented tuning tool, LARTTE, exhibits linear runtime and memory usage requirement, can effectively tune a circuit with over 15,000 variables and 8,000 constraints in under 7 minutes, and can minimize the probability of final delay variation by introducing a margin of separation between the worst output arrival time and all other outputs ’ arrival times. I.
Global and Local Optimization Algorithms for Optimal Signal Set Design
 Journal of Research of the National Institute of Standars and Technology
, 2001
"... this paper, we will assume a peak amplitude constraint, i.e.,  s m [t ] C , m =1,...,M , t =1,...,T , (3) where C > 0 is given. Note that we could just as easily have considered an average energy constraint in our formulation. Our design problem is thus reduced to choosing parameters in ..."
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this paper, we will assume a peak amplitude constraint, i.e.,  s m [t ] C , m =1,...,M , t =1,...,T , (3) where C > 0 is given. Note that we could just as easily have considered an average energy constraint in our formulation. Our design problem is thus reduced to choosing parameters in order to maximize Eq. (1), subject to the constraints Eq. (3)
LARGE SCALE SYSTEMS ISSUES IN MODELING COSTEFFECTIVE POLICIES FOR IMPROVING THE EUROPEAN AIR QUALITY
"... Abstract: The paper presents a large scale nonlinear model which is used for supporting international negotiations aimed at improving air quality in Europe. The model helps to identify costeffective measures for reducing air pollution emissions that will result in meeting environmental standards fo ..."
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Abstract: The paper presents a large scale nonlinear model which is used for supporting international negotiations aimed at improving air quality in Europe. The model helps to identify costeffective measures for reducing air pollution emissions that will result in meeting environmental standards for tropospheric ozone, acidification and eutrophication. Several methodological issues related to the specification, generation and optimizationbased analysis of large nonlinear models for decision support that are of a more general interest are presented. Copyright c○1998 IFAC