scholarly journals Recursive quadratic programming for constrained nonlinear optimization of session throughput in multiple‐flow network topologies

2020 ◽  
Vol 2 (6) ◽  
Author(s):  
Ridhima Mehta
Keyword(s):  
Quadratic Programming ◽  
Nonlinear Optimization ◽  
Flow Network ◽  
Constrained Nonlinear Optimization ◽  
Recursive Quadratic Programming ◽  
Network Topologies

Monotonicity Analysis and Recursive Quadratic Programming in Constrained Optimization

1985 ◽  
Vol 107 (4) ◽  
pp. 459-462 ◽  
Author(s):  
J. Zhou ◽  
R. W. Mayne
Keyword(s):  
Quadratic Programming ◽  
Constrained Optimization ◽  
Nonlinear Optimization ◽  
Active Set ◽  
Active Set Strategy ◽  
Constrained Nonlinear Optimization ◽  
Recursive Quadratic Programming ◽  
Analysis Strategy ◽  
Original Procedure ◽  
Monotonicity Analysis

This paper considers the use of an active set strategy based on monotonicity analysis as an integral part of a recursive quadratic programming (RQP) algorithm for constrained nonlinear optimization. Biggs’ RQP method employing equality constrained subproblems is the basis for the algorithm developed here and requires active set information. The monotonicity analysis strategy is applied to the sequence of search directions selected by the RQP method. As each direction is considered, progress toward optimum occurs and a new constraint is added to the active set. As the active set is finalized the basic RQP method is followed unless a constraint is to be dropped. Testing of the proposed algorithm illustrates its promise as an enhancement to Biggs’ original procedure.

Optimization With Discrete Variables Via Recursive Quadratic Programming: Part 2—Algorithm and Results

1989 ◽  
Vol 111 (1) ◽  
pp. 130-136 ◽  
Author(s):  
J. Z. Cha ◽  
R. W. Mayne
Keyword(s):  
Quadratic Programming ◽  
Performance Comparison ◽  
Programming Algorithm ◽  
Discrete Variables ◽  
Contour Analysis ◽  
Recursive Quadratic Programming ◽  
Analysis Technique ◽  
Rank One ◽  
Symmetric Rank One ◽  
Monotonicity Analysis

A discrete recursive quadratic programming algorithm is developed for a class of mixed discrete constrained nonlinear programming (MDCNP) problems. The symmetric rank one (SR1) Hessian update formula is used to generate second order information. Also, strategies, such as the watchdog technique (WT), the monotonicity analysis technique (MA), the contour analysis technique (CA), and the restoration of feasibility have been considered. Heuristic aspects of handling discrete variables are treated via the concepts and convergence discussions of Part I. This paper summarizes the details of the algorithm and its implementation. Test results for 25 different problems are presented to allow evaluation of the approach and provide a basis for performance comparison. The results show that the suggested method is a promising one, efficient and robust for the MDCNP problem.

Prediction of Performance and Design via Optimization of Ducted Propellers Subject to Non-axisymmetric Inflows

2005 ◽  
Author(s):  
Spyros A. Kinnas ◽  
Hanseong Lee ◽  
Hua Gu ◽  
Yumin Deng
Keyword(s):  
Nonlinear Optimization ◽  
Pressure Coefficient ◽  
Optimization Method ◽  
Least Square ◽  
Maximum Efficiency ◽  
Design Parameters ◽  
Blade Design ◽  
Constrained Nonlinear Optimization ◽  
Nonlinear Optimization Method ◽  
Ducted Propellers

Recently developed methods at UT Austin for the analysis of open or ducted propellers are presented, and then coupled with a constrained nonlinear optimization method to design blades of open or ducted propellers for maximum efficiency satisfying the minimum pressure constraint for fully wetted case, or the specified maximum allowable cavity area for cavitating case. A vortex lattice method (named MPUF3A) is applied to analyze the unsteady cavitating performance of open or ducted propellers subject to non-axisymmetric inflows. A finite volume method based Euler solver (named GBFLOW) is applied to predict the flow field around the open or ducted propellers, coupled with MPUF-3A in order to determine the interaction of the propeller with the inflow (i.e. the effective wake) or with the duct. The blade design of open or ducted propeller is performed by using a constrained nonlinear optimization method (named CAVOPT-BASE), which uses a database of computed performance for a set of blade geometries constructed from a base-propeller. The performance is evaluated using MPUF-3A and GBFLOW. CAVOPT-BASE approximates the database using the least square method or the linear interpolation method, and generates the coefficients of polynomials based on the design parameters, such as pitch, chord, and camber. CAVOPT-BASE finally determines the optimum blade design parameters, so that the propeller produces the desired thrust for the given constraints on the pressure coefficient or the allowed amount of cavitation.

scholarly journals Second-Order Optimality and Beyond: Characterization and Evaluation Complexity in Convexly Constrained Nonlinear Optimization

2017 ◽  
Vol 18 (5) ◽  
pp. 1073-1107 ◽  
Author(s):  
Coralia Cartis ◽  
Nick I. M. Gould ◽  
Philippe L. Toint
Keyword(s):  
Nonlinear Optimization ◽  
Second Order ◽  
Constrained Nonlinear Optimization ◽  
Evaluation Complexity

New Theoretical Results on Recursive Quadratic Programming Algorithms

1998 ◽  
Vol 97 (2) ◽  
pp. 435-454 ◽  
Author(s):  
J. M. Martínez ◽  
L. T. Santos
Keyword(s):  
Quadratic Programming ◽  
Recursive Quadratic Programming ◽  
Programming Algorithms ◽  
Theoretical Results
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