Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 20 for “"Penalty functions"”.
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Optimization of steel frames via penalty functions
… to minimize the weight of steel frames using a penalty function technique. The program is developed and several example problems are analyzed. All structures are designed in accordance with the AISC code. One of the problems is also analyzed by the Fully Stressed Design method, and the penalty …
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The Use of Probabilistic Risk Functions and Linear Penalty Functions for Hospital Evacuation Planning
… duration minimization, manipulations of the risk functions for the risk minimization approach were searched in this thesis such that the resulting evacuation plans approach the minimal duration without rules for the assignments of patients to vehicle types. It is possible to create risk functions …
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Optimization of composite structures by genetic algorithms
… The influence on the genetic search of the penalty functions enforcing failure constraints is studied. Combining fixed and proportional penalty functions is found to be the most efficient strategy. Improved selection, mutation, and stack swap operators are proposed. The use of an operator …
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Mendelian and Non-Mendelian Ancestral Repair for Constrained Evolutionary Optimisation
… modified representation and operators, penalty functions and repair strategies. This thesis makes significant contributions to the topic of genetic repair and introduces a non-Mendelian repair operator that has been inspired by a naturally occurring genetic repair mechanism in the …
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Design of structurally-sound masonry buildings using 3D static analysis
… of masonry structures is modeled using a novel penalty formulation, assuming a rigid-block behavior of masonry. Two methods were developed that apply this model of feasibility to structural optimization. In the first approach, structural feasibility is introduced into procedural modeling of …
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Pseudonormality and a language multiplier theory for constrained optimization
… link between constraint qualifications and exact penalty functions. Our analysis also yields identification of different types of Lagrange multipliers. Under some convexity assumptions, we show that there exists a special Lagrange multiplier vector, called informative, which carries significant …
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Social Class and Capital Punishment: A Theoretical and Empirical Analysis
… this relationship contends that the death penalty functions as part of a wider ideological system of power and social control. Sporadic death sentences prop up ideological imagery of justice and safety without representing the state as unduly repressive, and thus allow expendable others …
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An Evolutionary Based Methodology for Representing and Evolving Structural Design Solutions
… and geometry dependent loading configurations, penalty functions, and multiple objectives were analyzed. The IRR GA did not require the definition of a ground structure or heuristic rules to add or remove structural elements. The IRR GA synthesis design method generated novel frame designs that …
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Plantwide Control System Design for IGCC Power Plants with CO2 Capture
… and unmeasured disturbances. Various objective functions can be considered for the control system design such as maximization of profit, maximization of the power produced, or minimization of the auxiliary power consumed in the plant. The design of such a control system can make the IGCC plant …
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Sparse Modeling of Grouped Line Spectra
… structure in the solution, different convex penalty functions are introduced into the optimization. The cost trade-off between fit and penalty is set by some user parameters, as to approximate the true number of spectral lines in the signal, which implies that the response variable will be …
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Neural Network Training and Inversion with a Bregman Learning Framework
… More specifically, we propose a family of loss (penalty) functions that are based on a tailored Bregman distance. We provide detailed mathematical analysis on the derived Bregman learning framework and propose a whole range of deterministic and stochastic optimisation strategies to enable solving …
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Mapping Bisulfite-Treated Short DNA Reads
… uses homopolymer run length for contextual gap penalty functions, since homopolymer runs cause errors in Ion Torrent reads. In conjunction with BisPin, this software performed well on real and simulated bisulfite Ion Torrent data and Illumina data. InfoTrim, a read trimmer with an entropy term, …
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Software for Multidisciplinary Design Optimization of Truss-Braced Wing Aircraft with Deep Learning based Transonic Flutter Prediction Model
… employs particle swarm optimization with penalty functions for exploring optimal Transonic Truss Braced Wing (TTBW) aircraft design, similar to the Boeing 737-800 type of mission with a cruise Mach of 0.8, a range of 3115 n miles, and 162 passengers, with two different objective functions, …
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A primal-dual conjugate subgradient algorithm for large- scale/specially structured linear programming problems
… a Lagrangian dual function and a primal penalty function which satisfies a flexible set of specified properties, in order to generate a sequence of primal and dual iterates which can be shown to converge to an optimal pair of primal and dual solutions. Besides producing both primal and …
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A new method of meshing in discontinuous deformation analysis (DDA)
… block. Contact between blocks is modelled using penalty functions, with Coulomb's friction law controlling sliding along block boundaries. Tests show that while DDA is not well suited to dynamic simulations where the velocities of blocks become large, it can model rock masses to a reasonable …
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Efficient capacity allocation in a collaborative air transportation system
… of modifying the subproblem objectives through a penalty function determined by a master "dual" problem, is employed in the Objective-Based Allocation Method (OBAM). It is shown that the proper choice of penalty function results in a method that performs well dynamically and, assuming each user …
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Approximate dynamic programming for large scale systems
… consider information relaxation and introducing penalty. The method delivers tight bounds by identifying the best penalty function among a parameterized class of penalty functions. We implement our method on a high-dimensional financial application, namely, optimal execution and demonstrate the …
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A penalty-free multi-objective evolutionary optimization approach for the design and rehabilitation of water distribution systems
… model is that it eliminates the need for ad-hoc penalty functions, additional "boundary search" parameters, or special constraint handling procedures. No operator intervention, parameter calibration and trial runs are required. Conceptually, the approach is straightforward and probably the …