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A comparative study of SQP-type algorithms for nonlinear and nonconvex mixed-integer optimization

MATHEMATICAL programming COMPUTATION 2012年第4期4卷 383-412页

作者： Exler, Oliver Lehmann, Thomas Schittkowski, Klaus Univ Bayreuth Dept Comp Sci D-95440 Bayreuth Germany Konrad Zuse Zentrum ZIB D-14195 Berlin Germany

We present numerical results of a comparative study of codes for nonlinear and nonconvex mixed-integer optimization. The underlying algorithms are based on sequential quadratic programming (SQP) with stabilization by trust-regions, linear outer approximations, and branch-and-bound techniques. The mixed-integer quadratic programming subproblems are solved by a branch-and-cut algorithm. Second order information is updated by a quasi-Newton update formula (BFGS) applied to the Lagrange function for continuous, but also for integer variables. We do not require that the model functions can be evaluated at fractional values of the integer variables. Thus, partial derivatives with respect to integer variables are replaced by descent directions obtained from function values at neighboring grid points, and the number of simulations or function evaluations, respectively, is our main performance criterion to measure the efficiency of a code. Numerical results are presented for a set of 100 academic mixed-integer test problems. Since not all of our test examples are convex, we reach the best-known solutions in about 90 % of the test runs, but at least feasible solutions in the other cases. The average number of function evaluations of the new mixed-integer SQP code is between 240 and 500 including those needed for one-or two-sided approximations of partial derivatives or descent directions, respectively. In addition, we present numerical results for a set of 55 test problems with some practical background in petroleum engineering.

关键词： MINLP Mixed-integer nonlinear programming SQP sequential quadratic programming Trust region method Linear outer approximation MIQP Mixed-integer quadratic programming Numerical algorithms Performance evaluation Mixed-integer test problems Engineering optimization

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Active-set Newton methods for mathematical programs with vanishing constraints

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2012年第2期53卷 425-452页

作者： Izmailov, A. F. Pogosyan, A. L. MSU OR Dept VMK Fac Moscow 119991 Russia

Mathematical programs with vanishing constraints constitute a new class of difficult optimization problems with important applications in optimal topology design of mechanical structures. Vanishing constraints usually violate standard constraint qualifications, which gives rise to serious difficulties in theoretical and numerical treatment of these problems. In this work, we suggest several globalization strategies for the active-set Newton-type methods developed earlier by the authors for this problem class, preserving superlinear convergence rate of these methods under weak assumptions. Preliminary numerical results demonstrate that our approach is rather promising and competitive with respect to the existing alternatives.

关键词： Mathematical program with vanishing constraints Constraint qualification Optimality condition Active-set method sequential quadratic programming Semismooth Newton method Global convergence

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Multi-Agent Based Optimal Power Flow Solution

Multi-Agent Based Optimal Power Flow Solution

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Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Leeton, Uthen Kulworawanichpong, Thanatchai Suranaree Univ Technol Sch Elect Engn Inst Engn Power Syst Res Unit Nakhon Ratchasima 30000 Thailand

ISBN: (纸本)9781457705472;9781457705465

This paper describes multi-agent based optimal power flow solution in which total production cost is used as the problem objective to be minimized. In this work, simulation of peer-to-peer device coordination has been developed using Java Agent Development (JADE) software package. JADE provides a FIPA-compliant agent platform and a package to develop multi-agent systems used in this paper. Six agent types are established. They are i) load agent ii) power generating plants agent, iii) transformer tap-setting agent iv) reactive power agent v) optimal load-flow agent and vi) management agent. In this paper each agent has been modeled as an intelligent agent, which joins to a container to form the multi agent system for solving optimal power flow problems. In this paper, the standard IEEE 6-bus test power system was employed. The results of this proposed system showed that the use of multi-agent systems enables possibility of applying optimal power flow in real-world applications.

关键词： optimal power flow multi-agent system sequential quadratic programming

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sequential Tuning of Power System Stabilizers for Improving the Small Signal Stability in Multi-machine Power Systems

Sequential Tuning of Power System Stabilizers for Improving ...

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World Congress on Engineering and Computer Science

作者： Mahabuba, A. Khan, M. Abdullah AL Ghurair Univ Dubai U Arab Emirates BS Abdur Rahman Univ Sci & Technol Madras Tamil Nadu India

ISBN: (纸本)9789881925244

This paper presents a sequential tuning of Power System Stabilizers (PSSs) for improving the damping of low frequency electro- mechanical oscillations in a multi-machine power system using parameter - constrained nonlinear optimization algorithm. This algorithm deals with optimization problem using a sequential quadratic programming. The main objective of this procedure is to shift the undamped poles to the left hand side of the s-plane. In the proposed work, the parameters of each PSS controller are determined by sequentially using non-linear optimization technique. The objective of the coordinated parameter tuning is to globally optimize the overall system damping performance by maximize the damping of all both local and inter area modes of oscillations. The results obtained from sequential coordinating tuning method validate the improvement in damping of the overall power system oscillations in an optimal manner. The time domain simulation results of multi-machine power system validate the effectiveness of the proposed approach. In this paper, 10- machine 39- bus New England system is used as the test system. Investigations revealed that the dynamic performance of the system with sequentially tuned PSS is superior to that obtained from the conventionally optimized PSS.

关键词： Coordinated tuning sequential tuning Power System Stabilizer (PSS) Non-linear Optimization sequential quadratic programming

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Topology optimization of planar truss structures with continuous element intersection and node stability constraints

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2012年第C7期226卷 1821-1831页

作者： Leng, Guojun Duan, Baoyan Xidian Univ Minist Educ Key Lab Elect Equipment Struct Design Xian 710071 Peoples R China

This article presents a general nonlinear formulation for the topology optimization of planar truss structures. The novelty of this article is that element intersection is described in terms of a continuous intersection factor. The Heaviside function is used to map the element cross-sectional area to intersection properties. Therefore, the intersection feature is described by a continuous and differentiable function. The topology optimization model is hence set as a ground-structure method by simultaneously including constraints on element intersection and cinematic stability of nodes. The latter is also described by a continuous function. Three test cases are presented to demonstrate the validity of the proposed approach. Unlike mixed integer programming, the number of design cycles does not change much as the number of design variables increases.

关键词： Topology optimization planar truss structures element intersection node stability filter function sequential quadratic programming

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Comparative Dynamic Response of a Optimized Single Link Flexible Manipulator

Comparative Dynamic Response of a Optimized Single Link Flex...

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2nd International Conference on Mechanical and Aerospace Engineering (ICMAE 2011)

作者： Mahto, S. Dixit, U. S. Indian Inst Technol Dept Mech Engn Gauhati India

ISBN: (纸本)9783037852620

In this work, comparative study for dynamic response is carried out for optimized single link flexible robotic manipulator under various types of excitations. Manipulator is considered as an Euler-Bernoulli beam and shape is optimized for circular area of cross-section. Finite element method is used to obtain fundamental frequency and sequential quadratic programming (SQP) is used for its maximization.

关键词： Shape Optimization Finite Element method sequential quadratic programming Dynamic Response

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A Hybrid Quantum-Inspired Particle Swarm Evolution Algorithm and SQP Method for Large-Scale Economic Dispatch Problems

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7th International Conference on Intelligent Computing (ICIC)

作者： Niu, Qun Zhou, Zhuo Zeng, Tingting Shanghai Univ Sch Mechatron Engn & Automat Shanghai Key Lab Power Stn Automat Technol Shanghai 200072 Peoples R China

ISBN: (纸本)9783642245527

This paper proposes a hybrid method QPSO-SQP, which combines a quantum-inspired particle swarm evolution algorithm(QPSO) and the sequential quadratic programming (SQP) method to solve large-scale economic dispatch problems(EDPs). Due to the combination of quantum rotation gates and the updating mechanism of PSO, the QPSO has strong search ability and fast convergence speed, therefore it is employed as a global searcher to obtain good solutions for EDPs. As SQP is a gradient-based nonlinear programming method, it is used as a local optimizer to fine tune the best result of the QPSO. The proposed QPSO-SQP is applied to two large-scale EDPs to validate its effectiveness. The experiment results show that the proposed QPSO-SQP can obtain high-quality solutions and produce a satisfactory performance among most existing techniques.

关键词： Economic dispatch problem large scale quantum-inspired particle swarm algorithm sequential quadratic programming

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Active-set Newton methods for mathematical programs with vanishing constraints

Active-set Newton methods for mathematical programs with van...

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Workshop on Non linear Optimization, Variational Inequalities and Equilibrium Problems

作者： Izmailov, A. F. Pogosyan, A. L. MSU OR Dept VMK Fac Moscow 119991 Russia

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Reentry Trajectory Optimization of Airbreathing Hypersonic Vehicles Based on Gauss Pseudospectral Method

Reentry Trajectory Optimization of Airbreathing Hypersonic V...

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International Conference on Manufacturing Science and Technology (ICMST 2011)

作者： Yang, Bo Sun, Shang Beijing Univ Aeronaut & Astronaut Sch Astronaut Beijing 100083 Peoples R China

ISBN: (纸本)9783037852958

According to the nonlinear, multivariable and multi-constraint features of the reentry trajectory optimization problem of airbreathing hypersonic vehicles, a suboptimal solution method is developed. The reentry trajectory generation is converted to a nonlinear programming (NLP) problem by using Gauss pseudospectral method (GPM). The state and control variables on Gauss nodes are chosen as parameters to be optimized and the minimum total heat absorption is chosen as the optimal performance index. Then the sequential quadratic programming (SQP) method is used to solve the NLP problem. The states of optimized trajectory are compared with the states obtained by the integral of kinetic equations. By simulating on an example of airbreathing hypersonic vehicles, it is demonstrated that the above method is not sensitive to the estimate of motion states and is easier to converge. And the method is effective to solve trajectory optimization problems.

关键词： Airbreathing Hypersonic Vehicle Trajectory Optimization Gauss Pseudospectral Method sequential quadratic programming Minimum Total Heat Absorption

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Component-Oriented Decomposition for Collaborative Optimization in Reinforcement Concrete Bridge Design

Component-Oriented Decomposition for Collaborative Optimizat...

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4th International Conference on Technology of Architecture and Structure (ICTAS 2011)

作者： Wang, Lian Fa Tang, Ai Ping Harbin Inst Technol Sch Civil Engn Harbin 150090 Peoples R China

ISBN: (纸本)9783037852798

In order to implement the bi-level optimization strategy-collaborative optimization (CO) to bridge design, bridge optimization design process is subdivided into three subsystems in terms of component-oriented decomposition: superstructure subsystem, bearing subsystem and substructure subsystem. For system level, target function is formulated with the total direct construction cost, and inequality constraints induced relaxation factors are adopted to relax the intersubsystem consistency constraints. For subsystems, target functions are formulated with discrepancy expressions and constraints are formulated according to corresponding codes demands respectively. The feasibility and validity of the proposed approach are examined with an optimization process of reinforcement concrete box girder bridge. Optimization results from proposed approach are compared with that from mono-discipline optimization. The proposed approach shows high computing efficiency than mono-discipline optimization methods when achieving same optimization results.

关键词： Collaborative Optimization Component-oriented decomposition Reinforcement concrete box girder bridge sequential quadratic programming Genetic Algorithm

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