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Integrative design, production, and marketing policy for a configurable product family

INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT 2021年第1期16卷 43-57页

作者： Ziaei, Mazaher Ketabi, Saeedeh Ghandehari, Mahsa Univ Isfahan Dept Management Esfahan Iran

The growing diversity in demand and the shorter life cycle of products necessitate integrating policies of design, production, and marketing to decide on which products, with which attributes should be designed and by which strategies should be supplied to the market. This necessity increases in the manufacturing of the Configurable Products Family (CPF) such as cars, laptops, cell phones. The existing decision-making models either do not deal with all the three policies or are not concerned with the main variables. This study aims to develop a profit maximization model to integrate policies for CPFs by optimizing the main variables: the product's configuration, supply policy of components, price, and warranty lengths for product's modules. A new demand function is developed for such decision-making as well. The model is mixed-integer nonlinear programming, so an adapted Particle Swarm Optimization (PSO) is applied to solve different numerical cases and perform several sensitivity analysis. The results depict significant changes in the company's policy and profitability due to applying the model. The findings can introduce new insights for managers and engineers and a focal point for researchers to run further studies.

关键词： Production (Configurable Product Family) warranty demand Function nonlinear programming meta-heuristic (PSO)

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Learning-based Optimal Control for End-to-End Human-Mars Entry, Powered-Descent, and Landing Mission

Learning-based Optimal Control for End-to-End Human-Mars Ent...

引用

AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： You, Sixong Wan, Changhuang Dai, Ran Rea, Jeremy R. Purdue Univ Sch Aeronaut & Astronaut 701 W Stadium Ave W Lafayette IN 47907 USA Ohio State Univ Dept Mech & Aerosp 201 W 19th Ave Columbus OH 43210 USA NASA Flight Mech & Trajectory Design Branch Johnson Space Ctr 2001 Nasa PkwyEG5 Houston TX 77058 USA

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

This paper investigates the end-to-end human-Mars entry, powered-descent, and landing (EDL) guidance problem by developing a learning-based real-time optimal control method to achieve the goal of precise and fuel-efficient planetary landing. First, the end-to-end EDL guidance problem is formulated as a multi-phase optimal control problem with different dynamics and constraints at each phase. Then the customized alternating direction method of multipliers (ADMM) is applied to solve the end-to-end EDL guidance problem with different initial states off-line. After that, based on the optimized off-line solutions, the learning-based real-time optimal control method is developed. To be specific, supported by the optimal control theory, the necessary conditions of optimality for the entry phase and powered-descent phase guidance are derived, respectively, which leads to two-point-boundary-value-problems (TPBVPs). We then identify critical parameters that can determine the complete solutions of the TPBVPs. To find the implicit relationship between the initial states and these critical parameters, deep neural networks are constructed to learn the values of these critical parameters in real-time with sufficient training data. Finally, the learning-based optimal control method is implemented in simulation cases to verify the effectiveness of the proposed method.

关键词： Optimal Control Theory Artificial Neural Network Boundary Value Problems Planetary Landing Powered Descent Guidance Ignition Timing nonlinear programming Fuel Consumption Lift Coefficient Flight Path Angle

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Solving Optimal Control Problems with Regional Insensitivities to Controls

Solving Optimal Control Problems with Regional Insensitiviti...

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AIAA Aviation Forum and Exposition

作者： Nolan, Sean M. DeLaurentis, Daniel Purdue Univ Aeronaut & Astronaut Engn W Lafayette IN 47904 USA

ISBN: (数字)9781624106101

ISBN: (纸本)9781624106101

Recent advancements have overcome many obstacles of using indirect methods to solve complex optimal control problems. Still, there exist several numerical issues that often prevent convergence to a solution. One of the issues occurs when the solution to a problem contains a region in which the cost functional is insenstitive to the control. When this occurs is often not clear, and common techniques to address other numerical issues do not help. By examining a problem that maximizes the range of a hypersonic glide vehicle, this paper develops a method to identify and mitigate the insensitivity issue. The method can easily identify where the issue occurs by observing the determinant of the second derivative of the Hamiltonian with respect to the control vector. Augmenting the path cost with a small control effort term enables the solver to converge with very little impact on the optimal cost.

关键词： Trajectory Optimization Hypersonic Glide Vehicle Flight Path Angle Lift Coefficient nonlinear programming Hypersonic Vehicles Python Earth Boundary Value Problems Digital Computers

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Compact Optimization Learning for AC Optimal Power Flow

arXiv

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arXiv 2023年

作者： Park, Seonho Chen, Wenbo Mak, Terrence W.K. Van Hentenryck, Pascal School of Industrial and Systems Engineering Georgia Institute of Technology AtlantaGA30332 United States

This paper reconsiders end-to-end learning approaches to the Optimal Power Flow (OPF). Existing methods, which learn the input/output mapping of the OPF, suffer from scalability issues due to the high dimensionality of the output space. This paper first shows that the space of optimal solutions can be significantly compressed using principal component analysis (PCA). It then proposes COMPACT LEARNING, a new method that learns in a subspace of the principal components and translates the vectors into the original output space. This compression reduces the number of trainable parameters substantially, improving scalability and effectiveness. COMPACT LEARNING is evaluated on a variety of test cases from the PGLib and a realistic French transmission system having renewable energy changes with up to 30,000 buses. The paper also shows that the output of COMPACT LEARNING can be used to warm-start an exact AC solver to restore feasibility, while bringing significant speed-ups. © 2023, CC BY-NC-ND.

关键词： nonlinear programming

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A Constraint Qualification for the Dislocationhyperbolic Augmented Lagrangian Algorithm

SSRN

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SSRN 2023年

作者： Ramirez, Lennin Mallma Maculan, Nelson Xavier, Adilson Elias Xavier, Vinicius Layter Federal University of Rio de Janeiro Rio de Janeiro Brazil Institute of Mathematics and Statistics Graduate Program in Computational Sciences Rio de Janeiro State University Rio de Janeiro Brazil

The dislocation hyperbolic augmented Lagrangian algorithm (DHALA) solves the inequality nonconvex optimization problem. We ensure that the sequence generated by DHALA converges to a Karush-Kuhn-Tucker (KKT) point under the Mangasarian-Fromovitz constraint qualification. In previous work about this algorithm, no constraint qualification was considered. Finally, we present some computational illustrations, to see how our algorithm works. © 2023, The Authors. All rights reserved.

关键词： nonlinear programming

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Inexact restoration for derivative-free expensive function minimization and applications

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2022年第0期410卷

作者： Birgin, E. . G. Krejic, N. Martinez, J. . M. Univ Sao Paulo Inst Math & Stat Dept Comp Sci Rua Matao 1010Cidade Univ BR-05508090 Sao Paulo SP Brazil Univ Novi Sad Fac Sci Dept Math & Informat Trg Dositeja Obradovica 4 Novi Sad 21000 Serbia Univ Estadual Campinas Inst Math Stat & Sci Comp IMECC Dept Appl Math BR-13083859 Campinas SP Brazil

The Inexact Restoration approach has proved to be an adequate tool for handling the problem of minimizing an expensive function within an arbitrary feasible set by using different degrees of precision. This framework allows one to obtain suitable convergence and complexity results for an approach that rationally combines low-and high-precision evaluations. In this paper we consider the case where the domain of the optimization problem is an abstract metric space. Assumptions about differentiability or even continuity will not be used in the general algorithm based on Inexact Restoration. Although optimization phases that rely on smoothness cannot be used in this case, basic convergence and complexity results are recovered. A new derivative-free optimization phase is defined and the subproblems that arise at this phase are solved using a regularization approach that takes advantage of different notions of stationarity. The new methodology is applied to the problem of reproducing a controlled experiment that mimics the failure of a dam. (c) 2022 Elsevier B.V. All rights reserved.

关键词： nonlinear programming Inexact restoration Derivative-free Inexact evaluation of expensive function Algorithms

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Computational design and experimental testing of a flexible bi-stable airfoil for passive flow control

Computational design and experimental testing of a flexible ...

引用

AIAA Aviation Forum and Exposition

作者： Bhattacharyya, Anurag Bashqawi, Mark Kim, Se Yeon Zheng, Wanzheng Saxton-Fox, Theresa James, Kai Univ Illinois Dept Aerosp Engn 104 S Wright St Urbana IL 61801 USA

ISBN: (数字)9781624106101

ISBN: (纸本)9781624106101

This study focuses on the design of a novel airfoil camber morphing mechanism using topology optimization that aims to harness the flow field around the airfoil for its actuation. The morphing mechanism is designed using snap-through instabilities for actuation and shape change. The aerodynamic forces on the outer mold line are predicted using a panel method for inviscid effects and Thwaites method for the boundary layer. The results of the computational morphing airfoil design and the predicted aerodynamics are presented. A 3D printed model of the airfoil is tested in a wind tunnel to analyse its camber morphing characteristics.

关键词： Cambered Airfoil Boundary Layer Equations Aerodynamic Characteristics Airfoil Geometry Wind Tunnel Tests nonlinear programming Morphing Mechanisms Critical Angle of Attack Finite Element Analysis Fluid Structure Interaction

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Six-Dimensional Atmosphere Entry Guidance based on Dual Quaternion

Six-Dimensional Atmosphere Entry Guidance based on Dual Quat...

引用

AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Wan, Changhuang Pei, Chaoying Dai, Ran Jing, Gangshan Rea, Jeremy R. Ohio State Univ Dept Mech & Aerosp Engn Columbus OH 43210 USA Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47907 USA North Carolina State Univ Dept Elect & Comp Engn Raleigh NC 27607 USA NASA Johnson Space Ctr Flight Mech & Trajectory Design Branch 2001 NASA PkwyEG5 Houston TX 77058 USA

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

This paper investigates the six-degree-of-freedom (6-DoF) entry guidance problem for the Human Mars exploration mission. For the Human-scale entry, powered descent, and landing mission, it is required to use aerodynamic forces to decelerate the vehicle during the entry phase. Instead of assuming the entry vehicle as a point mass, we consider both the translational and rotational dynamics. Specifically, the 6-DoF rigid body kinematics and dynamics of the entry vehicle are represented by unit dual quaternions, which reduces the non-linearity of dynamic equations comparing with the Euler angle based dynamical model. Moreover, the equivalence between the dual quaternion based and Euler angle based models is analyzed. Then, the optimal entry guidance problem is formulated to minimize the terminal speed subject to the dual quaternion based dynamics, operational and mission constraints, including heating rate and the normal load of the entry vehicle. By using a discretization technique and polynomial approximation, the optimal entry guidance problem is reformulated into a nonconvex quadratically constrained quadratic program (QCQP) problem, which is solved via a customized alternating direction method of multipliers (ADMM). The accuracy of the dual quaternion based model and the computational efficiency of the ADMM algorithm are verified via numerical simulations.

关键词： Quaternions Euler Angles Aerodynamic Moments Three Degrees of Freedom Quadratic programming Mars Exploration Numerical Simulation nonlinear programming Trajectory Optimization Angle of Attack

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(Re)Constructing the European Economic Sentiment Indicator: An Optimization Approach

引用

SOCIAL INDICATORS RESEARCH 2021年第3期155卷 939-958页

作者： Lukac, Zrinka Cizmesija, Mirjana Univ Zagreb Fac Econ & Business Zagreb Grad Zagreb Croatia

The last recession in Europe has shown us that econometric models that factor in the qualitative perceptions and expectations of businesses and consumers-along with commonly used quantitative macroeconomic variables-can produce better results in explaining and forecasting economic activity. The European Commission's Business and Consumer Surveys (BCS) conducted by the European Commission (EC) are high-quality source for this kind of "soft" variables. One of the composite indicators based on BCS is the economic sentiment indicator (ESI), which is the main leading indicator for overall economic activity. We propose two new models for constructing the ESI. The first model is based on minimizing the sum of absolute values of estimation errors. The second model is based on maximizing the number of correctly predicted directions of change for GDP growth rates. Rather than using the EC's official standardization procedure for data, our models use "raw" data, thus simplifying the process of preparing the data. The models were tested for various prognostic horizons (up to four quarters in advance), using aggregated quarterly data for the European Union from 1996Q4 to 2019Q2. The results show that our new models significantly improve the ESI's predictive power, especially in predicting the direction of change of GDP growth rates, which is the main purpose of the BCS indicators. The best results are obtained for predictions made up to one quarter in advance, for which the second model correctly predicts the direction of change of GDP growth rates in 78.89% of cases versus the official ESI's 65.56%.

关键词： Forecasting Economic sentiment indicator Business and consumer surveys nonlinear programming

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Advanced-multi-step Moving Horizon Estimation 16

Advanced-multi-step Moving Horizon Estimation

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16th IFAC Symposium on Advanced Control of Chemical Processes (ADCHEM)

作者： Kim, Yeonsoo Lin, Kuan-Han Thierry, David M. Biegler, Lorenz T. Kwangwoon Univ Dept Chem Engn 20 Kwangwoon Ro Seoul 01897 South Korea Carnegie Mellon Univ Chem Engn Dept Pittsburgh PA 15213 USA

Moving Horizon Estimation (MHE) is an important optimization-based approach for state estimation and parameter updates, because of its capabilities in dealing with nonlinearity and state constraints. In addition, one of the applications is to provide the full state information for Model Predictive Controller (MPC) to control the process in either setpoint tracking or economic control purposes. However, the computational burden of MHE could deteriorate the control performance if the feedback delay caused by computation is too long, leading to potential safety issues or process damage. In this paper, we propose a fast moving horizon estimation algorithm to overcome the long computational time of MHE for real-time control applications, especially for fast dynamics or large-scale systems. We exploit the nonlinear programming (NLP) sensitivity and make use of efficient NLP solvers, IPOPT and k aug, to reduce the on-line computational costs. This new approach is demonstrated on a CSTR process, where results are compared to ideal MHE and advanced-step MHE (asMHE). Copyright (C) 2021 The Authors.

关键词： Estimation Algorithms Optimal Estimation nonlinear programming Sensitivity Analysis Real-time

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