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The Study of Algorithms with Filter for Inequality Constrained Optimization

Author: WangXiangLing
Tutor: ZhuZhiBin
School: Guilin University of Electronic Science and Technology
Course: Operational Research and Cybernetics
Keywords: Inequality constrained optimization Sequential Quadratic Programming Step Filters Global Convergence
CLC: O224
Type: Master's thesis
Year: 2011
Downloads: 29
Quote: 0
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Abstract


Pat on the computer 's move , the constrained optimization problems exist economic planning , engineering design, production pipe buried , transportation and other aspects have been widely applied to become a very active discipline So how solving constrained optimization problems become Optimization Field an important research area constrained optimization problem solving filter Algorithm enough about books optimization problems is one of the most effective methods , which meet in 1997 the world famous optimization experts R.Fletcher proposed method avoids the problem of solving the penalty parameter for solving constrained optimization problems effectively provide a new way to filter Algorithm the basic idea enough : in order to get the next trial step , the need to reduce the objective function value or constraint violation if the value of the objective function and constraints are worse ( ie, a few standard function value and constraint violation at any point than before large ) , then the point is as small successful iteration point _ otherwise, the point is as successful iteration point paper presents two ideas to solve using the filters and small constraint optimization problems efficient algorithms , as follows first proposed a step -based sequential quadratic programming (SQP) a filter Algorithm this algorithm is applied to the filter of France sQP methods towel function by reducing the constraint violation value and an approximation of a function of several objective function value to determine the tentative step foot station is small filters to accept this method with other filters France , it needs to reduce small trust region radius and foot by changing the step factor to ensure sufficient descent in nature and the . This method requires a small penalty parameter and select the initial point , but under certain conditions, to obtain a global convergence of the second , for the SQP method for solving nonlinear programming problems , gives a little under equality constraints filter SQP algorithm when r a planning (QP) sub-problem solution unbounded small -compliant or when appropriate through a linear programming problem Di was the optimal solution of this method need to select a small penalty function and H each iteration requires only one QP subproblem solutions can . Kept ' under certain conditions , the SQP method filters the last full global convergence of the algorithm for the numerical experiment results show that the algorithm is effective enough

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CLC: > Mathematical sciences and chemical > Mathematics > Operations Research > Optimization of the mathematical theory
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