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Churn management optimization with controllable marketing variables and associated management costs

EXPERT SYSTEMS WITH APPLICATIONS 2013年第6期40卷 2198-2207页

作者： Kim, Yong Seog Lee, Hyeseon Johnson, John D. Utah State Univ Dept Management Informat Syst Jon M Huntsman Sch Business Logan UT 84322 USA Pohang Univ Sci & Technol Ind & Management Dept Pohang 790784 South Korea

In this paper, we propose a chum management model based on a partial least square (PLS) optimization method that explicitly considers the management costs of controllable marketing variables for a successful churn management program. A PLS prediction model is first calibrated to estimate the churn probabilities of customers. Then this PLS prediction model is transformed into a control model after relative management costs of controllable marketing variables are estimated through a triangulation method. Finally, a PLS optimization model with marketing objectives and constraints are specified and solved via a sequential quadratic programming method. In our experiments, we observe that while the training and test data sets are dramatically different in terms of churner distributions (50% vs. 1.8%), four controllable variables in three marketing strategies significantly changed through optimization process while other variables only marginally changed. We also observe that the most significant variable in a PLS prediction model does not necessarily change most significantly in our PLS optimization model due to the highest management cost associated, implying differences between a prediction and an optimization model. Finally, two marketing models designed for targeting the subsets of customers based on churn probability or management costs are presented and discussed. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Churn management PLS prediction model PLS optimization model Management cost Triangulation sequential quadratic programming

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Optimal motion planning of redundant manipulators with controlled task infeasibility

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MECHANISM AND MACHINE THEORY 2013年 64卷 155-174页

作者： Kim, Joo H. Joo, Chang B. NYU Polytech Inst Dept Mech & Aerosp Engn Brooklyn NY USA

In optimal motion planning and control, the complex time-varying nature of redundant robots, environments, and task requirements causes complex domains and conflicting constraints. Since predicting or recovering infeasibility is not always possible, infeasibilities occur frequently and are not completely avoidable. We introduce a constrained nonlinear programming framework of controlled (as opposed to recovered) infeasibility for physically valid solutions while preserving the original problem and variable space. The constraint prioritization hierarchy includes a comprehensive classification of physical consistency, design requirements, and tasks. Priority weight functions having features of normalization and prioritization are incorporated into a sequential quadratic programming (SQP) algorithm to ensure generality and strict satisfaction of high-priority constraints, while lower-priority constraint violations are minimized. These are embedded in SQP through its merit function and composite cost function, in which general nonlinear functions including unilateral, time-dependent, and nonholonomic, can be incorporated in a unified approach. Also, the avoidance of the discontinuity problem with unilateral constraints is due to the time-dependent constraints strategy, which actively adapts to varying states. Numerical examples using multibody dynamic models of a redundant manipulator demonstrate these advantages. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Constraint prioritization Controlled infeasibility Normalization Optimal motion planning Redundant robot sequential quadratic programming

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A very simple SQCQP method for a class of smooth convex constrained minimization problems with nice convergence results

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MATHEMATICAL programming 2013年第1-2期142卷 349-369页

作者： Auslender, Alfred Univ Lyon 1 Inst Camille Jordan F-69365 Lyon France Ecole Polytech Dept Econ F-75230 Paris France

We introduce a new and very simple algorithm for a class of smooth convex constrained minimization problems which is an iterative scheme related to sequential quadratically constrained quadratic programming methods, called sequential simple quadratic method (SSQM). The computational simplicity of SSQM, which uses first-order information, makes it suitable for large scale problems. Theoretical results under standard assumptions are given proving that the whole sequence built by the algorithm converges to a solution and becomes feasible after a finite number of iterations. When in addition the objective function is strongly convex then asymptotic linear rate of convergence is established.

关键词： Smooth convex constrained minimization quadratically constrained quadratic programming sequential quadratic programming Convergence rate Optimal projected gradient schemes

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Optimal Free-Return Trajectories to Near-Earth Asteroids

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2013年第5期36卷 1346-1355页

作者： Bradley, Nicholas Ocampo, Cesar Univ Texas Austin Dept Aerosp Engn & Engn Mech WRW Labs Austin TX 78712 USA

A method is presented to calculate optimal trajectories to near-Earth asteroids that incorporate free-return trajectory segments. These trajectories are useful because they return to Earth with no fuel penalty, which is useful for risk mitigation on manned missions. The algorithm minimizes total velocity change over an entire nominal mission, encompassing a single impulsive maneuver each for Earth departure, leaving the free-return trajectory, rendezvous with and departure from the asteroid, culminating with unpowered reentry into Earth's atmosphere. Two example cases are presented in the circular restricted three-body model: a mission to 2000 SG344 from 23 August 2028 to 9 October 2029 with a cost of 5.307 km/s, and a mission to 2006 BZ147 from 9 February 2033 to 21 December 2033 with a cost of 7.000 km /s. The results presented here showcase the usage of the algorithm, which may be applied to free-return trajectories to a wide variety of near-Earth objects.

关键词： Free Return Trajectory Asteroids Earth Earth Atmosphere Flight Path Angle Parking Orbit Asteroid Missions Propellant sequential quadratic programming Planetary Science

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Maximum Volume Clustering: A New Discriminative Clustering Approach

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JOURNAL OF MACHINE LEARNING RESEARCH 2013年 14卷 2641-2687页

作者： Niu, Gang Dai, Bo Shang, Lin Sugiyama, Masashi Tokyo Inst Technol Dept Comp Sci Meguro Ku Tokyo 1528552 Japan Georgia Inst Technol Coll Comp Atlanta GA 30332 USA Nanjing Univ State Key Lab Novel Software Technol Nanjing 210023 Jiangsu Peoples R China

The large volume principle proposed by Vladimir Vapnik, which advocates that hypotheses lying in an equivalence class with a larger volume are more preferable, is a useful alternative to the large margin principle. In this paper, we introduce a new discriminative clustering model based on the large volume principle called maximum volume clustering (MVC), and then propose two approximation schemes to solve this MVC model: A soft-label MVC method using sequential quadratic programming and a hard-label MVC method using semi-definite programming, respectively. The proposed MVC is theoretically advantageous for three reasons. The optimization involved in hard-label MVC is convex, and under mild conditions, the optimization involved in soft-label MVC is akin to a convex one in terms of the resulting clusters. Secondly, the soft-label MVC method possesses a clustering error bound. Thirdly, MVC includes the optimization problems of a spectral clustering, two relaxed k-means clustering and an information-maximization clustering as special limit cases when its regularization parameter goes to infinity. Experiments on several artificial and benchmark data sets demonstrate that the proposed MVC compares favorably with state-of-the-art clustering methods.

关键词： discriminative clustering large volume principle sequential quadratic programming semi-definite programming finite sample stability clustering error bound

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Numerical shape optimization of a confined cavity in natural convection regime

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COMPUTERS & FLUIDS 2013年 75卷 11-21页

作者： Aounallah, M. Belkadi, M. Adjlout, L. Imine, O. LAHN Univ Sci & Technol dOran Mohamed Boudiaf Lab Aerohydrodynam Navale USTOMB El Mnaouar 31000 Oran Algeria LASP Univ Sci & Technol dOran Mohamed Boudiaf Lab Aeronaut & Syst Propulsifs USTOMB El Mnaouar 31000 Oran Algeria

The aim of this work is to optimize the geometric shape in enclosures similar to the square cavity in natural convection regime. The desired configuration differs from the classical cavity by the geometrical form of the hot wall to be defined. The procedure is based on a sequential quadratic programming in which the wall is parameterized by Bezier curves. The numerical optimization method developed is the outcome of combining a flow calculation method and a constrained minimization method. Investigations have been performed for different inclination angles and various Rayleigh numbers. The numerical results show that optimization is relevant since the heat transfer rate decreases considerably by comparison with the square and the undulated cavities. It is also found that the beneficial optimization occurs for high Rayleigh numbers. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Optimization sequential quadratic programming Natural convection Cavity Bezier curves

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Structural optimization technique of a T-tail

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING 2013年第G6期227卷 1009-1020页

作者： Qiu, Ju Sun, Qin Northwestern Polytech Univ Sch Aeronaut Xian 710072 Peoples R China

A T-tail's structural design is a complex engineering problem, and multiple factors are often taken into consideration, especially flutter failure. This approach combining sequential quadratic programming and multi-island genetic algorithm handles this design problem. In the first stage, the use of sequential quadratic programming can rapidly assist in initial design by obtaining a proper model for the next optimization, with the weight as an optimization goal, subjected to constraints in conventional performance. In the second stage, multi-island genetic algorithm is used to optimize the previous result model with special requirements, mainly referring to flutter speed. The optimization-analysis results are compared and discussed with insight into the use of sequential quadratic programming and multi-island genetic algorithm. In light of the second optimization, the special flutter performance of the T-tail is illustrated, again. Improving the torsional stiffness of the horizontal tail increases the flutter speed.

关键词： T-tail optimization technique flutter characteristics sequential quadratic programming multi-island genetic algorithm

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An inexact restoration strategy for the globalization of the sSQP method

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2013年第3期54卷 595-617页

作者： Fernandez, D. Pilotta, E. A. Torres, G. A. Univ Nacl Cordoba Fac Matemat Astron & Fis CIEM CONICET RA-5000 Cordoba Argentina

A globally convergent algorithm based on the stabilized sequential quadratic programming (sSQP) method is presented in order to solve optimization problems with equality constraints and bounds. This formulation has attractive features in the sense that constraint qualifications are not needed at all. In contrast with classic globalization strategies for Newton-like methods, we do not make use of merit functions. Our scheme is based on performing corrections on the solutions of the subproblems by using an inexact restoration procedure. The presented method is well defined and any accumulation point of the generated primal sequence is either a Karush-Kuhn-Tucker point or a stationary (maybe feasible) point of the problem of minimizing the infeasibility. Also, under suitable hypotheses, the sequence generated by the algorithm converges Q-linearly. Numerical experiments are given to confirm theoretical results.

关键词： sequential quadratic programming Nonlinear programming Global convergence Augmented Lagrangian

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A restoration-free filter SQP algorithm for equality constrained optimization

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APPLIED MATHEMATICS AND COMPUTATION 2013年第11期219卷 6016-6029页

作者： Zhu, Xiaojing Pu, Dingguo Tongji Univ Dept Math Shanghai 200092 Peoples R China

In this paper, a trust-region sequential quadratic programming algorithm with a modified filter acceptance mechanism is proposed for nonlinear equality constrained optimization. The most important advantage of the proposed algorithm is its avoidance of any feasibility restoration phase, a necessity in traditional filter methods. We solve quadratic programming subproblems based on the well-known Byrd-Omojokun trust-region method. Inexact solutions to these subproblems are allowed. Under some standard assumptions, global convergence of the proposed algorithm is established. Numerical results show our approach is potentially useful. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Constrained optimization sequential quadratic programming Filter Feasibility restoration

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Hybrid algorithm for dynamic economic dispatch with valve-point effects

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IET GENERATION TRANSMISSION & DISTRIBUTION 2013年第10期7卷 1096-1104页

作者： Chen, Yan Wen, Jinyu Jiang, Lin Cheng, Shijie Huazhong Univ Sci & Technol State Key Lab Adv Electromagnet Engn & Technol Wuhan 430074 Peoples R China Univ Liverpool Dept Elect Engn & Elect Liverpool L69 3GJ Merseyside England

Dynamic economic dispatch problem in power system considering valve-point effects of generators is a non-smooth, non-convex and multi-dimensional constrained optimisation problem. In allusion to those characteristics, this study proposes a hybrid algorithm which integrates low-discrepancy sequences, improved shuffled frog leaping algorithm and sequential quadratic programming. The effectiveness of the proposed method has been verified by using case studies based on 5-unit, 10-unit and 30-unit test systems over a period of 24 h. The results show that the proposed method has improved solution quality and computation efficiency, compared with most current approaches.

关键词： concave programming power generation dispatch power generation economics quadratic programming time 24 h test systems sequential quadratic programming improved shuffled frog leaping algorithm low-discrepancy sequences nonsmooth optimisation problem nonconvex optimisation problem multidimensional constrained optimisation problem generators power system dynamic economic dispatch problem valve-point effects hybrid algorithm

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