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Journal articles on the topic 'Nonlinear program (NLP)'

Author: Grafiati

Published: 4 June 2025

Last updated: 14 July 2025

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1

Isaza Hurtado, Jhon Alexander, Diego A. Muñoz, and Hernán Álvarez. "Efficient solution of nonlinear model predictive control by a restricted enumeration method." Enfoque UTE 9, no. 4 (2018): 13–23. http://dx.doi.org/10.29019/enfoqueute.v9n4.393.

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This work presents an alternative method to solve the nonlinear program (NLP) for nonlinear model predictive control (NMPC) problems. The NLP is the most computational demanding task in NMPC, which limits the industrial implementation of this control strategy. Therefore, it is important to consider algorithms that can solve the nonlinear program, not only in real time but also guaranteeing feasibility. In this work, the restricted enumeration method is proposed as alternative to solve the NLP for NMPC problems, showing successful results for pH control in a sugar cane process plant. This metho

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2

Lim, Dae Young, Xuan Zhou, and Kil To Chong. "The Optimization of Traffic Signal Control Using LP and NLP." Applied Mechanics and Materials 321-324 (June 2013): 2241–45. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.2241.

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This paper develops a new algorithm for the dynamic intersection control based on linear and nonlinear program. A new set of formula based on geometric construction are proposed to estimate the steady-and-oversaturation delay, which occasionally have the only one kind of controllable variable of the green splits. As a dynamic model, it can automatically adjust the split green ratio to achieve the minimal delay.Since the objective function of over-saturation delay is linear and under-saturation delay is nonlinear, the combination of linear and nonlinear program can be applied to either over-sat

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3

Lugar, Daniel J., and Ganesh Sriram. "Isotope-assisted metabolic flux analysis as an equality-constrained nonlinear program for improved scalability and robustness." PLOS Computational Biology 18, no. 3 (2022): e1009831. http://dx.doi.org/10.1371/journal.pcbi.1009831.

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Stable isotope-assisted metabolic flux analysis (MFA) is a powerful method to estimate carbon flow and partitioning in metabolic networks. At its core, MFA is a parameter estimation problem wherein the fluxes and metabolite pool sizes are model parameters that are estimated, via optimization, to account for measurements of steady-state or isotopically-nonstationary isotope labeling patterns. As MFA problems advance in scale, they require efficient computational methods for fast and robust convergence. The structure of the MFA problem enables it to be cast as an equality-constrained nonlinear p

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4

Tamimi, Jasem. "Choosing the number of time intervals for solving a model predictive control problem of nonlinear systems." Transactions of the Institute of Measurement and Control 43, no. 12 (2021): 2799–808. http://dx.doi.org/10.1177/01423312211007315.

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Model predictive control (MPC) is a control strategy that can handle state and control multi-variables at same time. To use the MPC using direct methods for solving the a dynamic optimization problem, one needs, for example, to transform the optimization problem into a nonlinear programming (NLP) problem by dividing the prediction horizon into equal time intervals. In this work, we suggest a tool and procedures for helping to choose a ‘compromise’ number of time intervals with a needed accuracy, objective cost, number of turned NLP iterations and computational time. On the other hand, we offer

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5

Ralph, Daniel. "Mathematical programs with complementarity constraints in traffic and telecommunications networks." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 366, no. 1872 (2008): 1973–87. http://dx.doi.org/10.1098/rsta.2008.0026.

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Given a suitably parametrized family of equilibrium models and a higher level criterion by which to measure an equilibrium state, mathematical programs with equilibrium constraints (MPECs) provide a framework for improving or optimizing the equilibrium state. An example is toll design in traffic networks, which attempts to reduce total travel time by choosing which arcs to toll and what toll levels to impose. Here, a Wardrop equilibrium describes the traffic response to each toll design. Communication networks also have a deep literature on equilibrium flows that suggest some MPECs. We focus o

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Pham, Duc Dai. "Optimal Pressure Management for Large-Scale Water Distribution Systems Using Smoothing Model." Journal of Science and Technology - Technical Universities 30.8, no. 147 (2020): 34–39. http://dx.doi.org/10.51316/30.8.6.

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Optimal pressure management in water distribution systems (WDSs) is one of the most efficient approaches to control water leakage for water utilities worldwide. The optimal pressure management can be accomplished through regulating operations of pressure reducing valves (PRVs) to ensure that the excessive pressure in the WDS is minimized. This engineering task can be casted into a nonlinear program problem (NLP) with non-smooth constraints. Until now, the non-smooth constraints have been approximated by the smoothing function of Chen Harker-Kanzow-Smale (CHKS). In this paper, instead of using

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7

Sadek, Adel W., Brian L. Smith, and Michael J. Demetsky. "Dynamic Traffic Assignment: Genetic Algorithms Approach." Transportation Research Record: Journal of the Transportation Research Board 1588, no. 1 (1997): 95–103. http://dx.doi.org/10.3141/1588-12.

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Real-time route guidance is a promising approach to alleviating congestion on the nation’s highways. A dynamic traffic assignment model is central to the development of guidance strategies. The artificial intelligence technique of genetic algorithms (GAs) is used to solve a dynamic traffic assignment model developed for a real-world routing scenario in Hampton Roads, Virginia. The results of the GA approach are presented and discussed, and the performance of the GA program is compared with an example of commercially available nonlinear programming (NLP) software. Among the main conclusions is

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Zhang, Ke Nan, and Wan Chun Chen. "Trajectory Optimization for Hypersonic Vehicle Satisfying Maneuvering Penetration." Applied Mechanics and Materials 110-116 (October 2011): 5223–31. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.5223.

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A trajectory optimization method for hypersonic vehicle in glide phase satisfying maneuvering penetration is proposed. Divide the dangerous zones that the hypersonic vehicle may encounter during glide phase into avoidable no-fly zones and avoidless no-fly zones. Take the avoidable no-fly zones as path constraints to join the trajectory optimization. To penetrate the avoidless no-fly zones, trajectory is programmed by some maneuvering policy. Direct shooting method is used to discretize the control variable to piecewise constant functions. So the optimal control problem is transferred to a nonl

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9

Tangaramvong, Sawekchai, and Francis Tin-Loi. "Optimal Retrofitting of Structures Using Braces." Applied Mechanics and Materials 553 (May 2014): 807–12. http://dx.doi.org/10.4028/www.scientific.net/amm.553.807.

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The paper presents a mathematical programming based approach for the efficient retrofitting, with braces, of structures subjected to multiple load cases and serviceability limitations, simultaneously. The method is based on a simple ground structure concept that generates within a design domain all possible cross braces, and then automates the decision as to which brace members are retained or eliminated using unknown 0-1 variables. The optimization minimizes simultaneously the total number and volume of design braces. The governing problem takes the form of a disjunctive and combinatorial opt

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10

Rodman, Alistair D., Samir Diab, and Dimitrios I. Gerogiorgis. "Dynamic Optimization of a Fed-Batch Nosiheptide Reactor." Processes 8, no. 5 (2020): 587. http://dx.doi.org/10.3390/pr8050587.

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Nosiheptide is a sulfur-containing peptide antibiotic, showing exceptional activity against critical pathogens such as methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE) with livestock applications that can be synthesized via fed-batch fermentation. A simplified mechanistic fed-batch fermentation model for nosiheptide production considers temperature- and pH-dependence of biomass growth, substrate consumption, nosiheptide production and oxygen mass transfer into the broth. Herein, we perform dynamic simulation over a broad range of possible feeding po

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11

Kaliyaperumal, Palanivel, and Amrit Das. "A Mathematical Model for Nonlinear Optimization Which Attempts Membership Functions to Address the Uncertainties." Mathematics 10, no. 10 (2022): 1743. http://dx.doi.org/10.3390/math10101743.

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The problem of optimizing an objective function that exists within the constraints of equality and inequality is addressed by nonlinear programming (NLP). A linear program exists if all of the functions are linear; otherwise, the problem is referred to as a nonlinear program. The development of highly efficient and robust linear programming (LP) algorithms and software, the advent of high-speed computers, and practitioners’ wider understanding and portability of mathematical modeling and analysis have all contributed to LP’s importance in solving problems in a variety of fields. However, due t

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12

Aggarwal, Rachit, Mrinal Kumar, Rachel E Keil, and Anil V. Rao. "Chance-constrained path planning in narrow spaces for a dubins vehicle." International Robotics & Automation Journal 7, no. 2 (2021): 46–61. http://dx.doi.org/10.15406/iratj.2021.07.00277.

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The problem of optimal path planning through narrow spaces in an unstructured environment is considered. The optimal path planning problem for a Dubins agent is formulated as a chance-constrained optimal control problem (CCOCP), wherein the uncertainty in obstacle boundaries is modelled using standard probability distributions. The chance constraints are transformed to deterministic equivalents using the inverse cumulative distribution function and subsequently incorporated into a deterministic optimal control problem. Due to multiple convex sub-regions introduced by the obstacles, the initial

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13

Cai, Yifei, Jun Chen, Da Lei, and Jiang Yu. "The Integration of Multimodal Networks: The Generalized Modal Split and Collaborative Optimization of Transportation Hubs." Journal of Advanced Transportation 2022 (December 13, 2022): 1–32. http://dx.doi.org/10.1155/2022/3442921.

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Integrated transportation is one of the most important methods to encourage the modal shift from car to public transportation (PT). However, as most cities have an existing multimodal network, it is difficult to expand the current networks by building more PT routes. Thus, integrating different modes through the optimization of hubs is a cost-efficient way to promote sustainable mobility. This paper develops a bilevel multimodal network design problem based on the collaborative optimization of urban transportation hubs. The upper-level problem is formulated as a mixed-integer nonlinear program

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14

Shoaib, Abeer M., Amr A. Atawia, Mohamed H. Hassanean, Abdelrahman G. Gadallah, and Ahmed A. Bhran. "Designing Water Inter-Plant Networks of Single and Multiple Contaminants through Mathematical Programming." Water 15, no. 24 (2023): 4315. http://dx.doi.org/10.3390/w15244315.

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Water is the meaning of life for humans, agricultural and industrial processes; controlling the distribution of water and wastewater between industrial processes is very vital for rationalizing water and preserving the environment. This paper addresses a mathematical approach to optimizing water inter-plant networks. The water network problem is formulated as a nonlinear program (NLP) that is solved by LINGO Software, version 14.0. A generalized two-step mathematical model is designed to be valid for solving networks containing large numbers of sources and sinks. The introduced model is propos

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15

Zanelli, A., A. Domahidi, J. Jerez, and M. Morari. "FORCES NLP: an efficient implementation of interior-point methods for multistage nonlinear nonconvex programs." International Journal of Control 93, no. 1 (2017): 13–29. http://dx.doi.org/10.1080/00207179.2017.1316017.

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16

El-Sobky, B., G. Ashry, and Y. Abo-Elnaga. "An active-set with barrier method and trust-region mechanism to solve a nonlinear Bilevel programming problem." AIMS Mathematics 7, no. 9 (2022): 16112–46. http://dx.doi.org/10.3934/math.2022882.

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<abstract><p>Nonlinear Bilevel programming (NBLP) problem is a hard problem and very difficult to be resolved by using the classical method. In this paper, Karush-Kuhn-Tucker (KKT) condition is used with Fischer-Burmeister function to convert NBLP problem to an equivalent smooth single objective nonlinear programming (SONP) problem. An active-set strategy is used with Barrier method and trust-region technique to solve the smooth SONP problem effectively and guarantee a convergence to optimal solution from any starting point. A global convergence theory for the active-set barrier tr

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17

Elsobky, Bothina, and Gehan Ashry. "An Active-Set Fischer–Burmeister Trust-Region Algorithm to Solve a Nonlinear Bilevel Optimization Problem." Fractal and Fractional 6, no. 8 (2022): 412. http://dx.doi.org/10.3390/fractalfract6080412.

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In this paper, the Fischer–Burmeister active-set trust-region (FBACTR) algorithm is introduced to solve the nonlinear bilevel programming problems. In FBACTR algorithm, a Karush–Kuhn–Tucker (KKT) condition is used with the Fischer–Burmeister function to transform a nonlinear bilevel programming (NBLP) problem into an equivalent smooth single objective nonlinear programming problem. To ensure global convergence for the FBACTR algorithm, an active-set strategy is used with a trust-region globalization strategy. The theory of global convergence for the FBACTR algorithm is presented. To clarify th

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18

El-Sobky, B., and G. Ashry. "An interior-point trust-region algorithm to solve a nonlinear bilevel programming problem." AIMS Mathematics 7, no. 4 (2022): 5534–62. http://dx.doi.org/10.3934/math.2022307.

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<abstract><p>In this paper, a nonlinear bilevel programming (NBLP) problem is transformed into an equivalent smooth single objective nonlinear programming (SONP) problem utilized slack variable with a Karush-Kuhn-Tucker (KKT) condition. To solve the equivalent smooth SONP problem effectively, an interior-point Newton's method with Das scaling matrix is used. This method is locally method and to guarantee convergence from any starting point, a trust-region strategy is used. The proposed algorithm is proved to be stable and capable of generating approximal optimal solution to the non

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19

Li, Yang Cheng, and Mei Gao. "Dynamic Elasto-Plastic Analysis of a High-Rise Hybrid Structure." Applied Mechanics and Materials 71-78 (July 2011): 266–69. http://dx.doi.org/10.4028/www.scientific.net/amm.71-78.266.

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Dynamic elasto-plastic analysis methods can actually indicate the characteristic of structure. This paper is concerned with the seismic performance evaluation of a super high-rise hybrid structure by using nonlinear dynamic procedure (NDP). By reasonable selection of input ground motions, the nonlinear dynamic analyses are carried out by using CANNY program. Then the seismic responses of hybrid structure under three different earthquake intensities are obtained. Comparing the responses of three levels with pre-established performance objective, the results show that all responses meet the requ

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20

Savonik, O. M. "Interval estimation of reliability indices from the results of complex system component tests." Technical mechanics 2023, no. 1 (2023): 105–14. http://dx.doi.org/10.15407/itm2023.01.105.

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The goal of this work is to find the lower estimate of the no-failure probability (NFP) of a complex monotonic nonrecoverable system from the results of independent binomial tests of its components. Using the general-and-probabilistic method, the NFP is considered as a probability function polynomial, which is a linear homogeneous polynomial in each of the S variables where S is the number of system component types. Based on the method of confidence sets, the NFP lower estimate is found as the minimum of a function of an unknown multidimensional parameter at a probability of the aggregate test

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21

Jhon, Alexander Isaza Hurtado, A. Muñoz Diego, and Álvarez Hernán. "Efficient solution of nonlinear model predictive control by a restricted enumeration metho." 9, no. 4 (2018): 13–23. https://doi.org/10.29019/enfoqueute.v9n4.393.

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Abstract This work presents an alternative method to solve the nonlinear program (NLP) for nonlinear model predictive control (NMPC) problems. The NLP is the most computational demanding task in NMPC, which limits the industrial implementation of this control strategy. Therefore, it is important to consider algorithms that can solve the nonlinear program, not only in real time but also guaranteeing feasibility. In this work, the restricted enumeration method is proposed as alternative to solve the NLP for NMPC problems, showing successful results for pH control in a sugar cane process plant. T

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22

Nurkanović, Armin, Anton Pozharskiy, and Moritz Diehl. "Solving Mathematical Programs with Complementarity Constraints Arising in Nonsmooth Optimal Control." Vietnam Journal of Mathematics, August 27, 2024. http://dx.doi.org/10.1007/s10013-024-00704-z.

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AbstractThis paper examines solution methods for mathematical programs with complementarity constraints (MPCC) obtained from the time-discretization of optimal control problems (OCPs) subject to nonsmooth dynamical systems. The MPCC theory and stationarity concepts are reviewed and summarized. The focus is on relaxation-based methods for MPCCs, which solve a (finite) sequence of more regular nonlinear programs (NLP), where a regularization/homotopy parameter is driven to zero. Such methods perform reasonably well on currently available benchmarks. However, these results do not always generaliz

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23

Yang, Qishun, MingLiang Song, Xiao Chen, Min Li, and Xiaoan Wang. "The influence of linear and nonlinear pedagogy on motor skill performance: the moderating role of adaptability." Frontiers in Psychology 16 (March 31, 2025). https://doi.org/10.3389/fpsyg.2025.1540821.

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This study addresses the gap in understanding the moderating role of adaptability in the effects of linear pedagogy (LP) and nonlinear pedagogy (NLP) on motor skill performance (MSP), particularly in dynamic sports environments. Recognizing the limited exploration of adaptability’s moderating role in existing literature, this research investigates how adaptability influences the effectiveness of these pedagogical strategies among college students. Forty university males students with no prior soccer experience were randomly assigned to LP or NLP groups and underwent an 8-week training program.

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Berthold, Timo, and Jakob Witzig. "Conflict Analysis for MINLP." INFORMS Journal on Computing, March 30, 2021. http://dx.doi.org/10.1287/ijoc.2020.1050.

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The generalization of mixed integer program (MIP) techniques to deal with nonlinear, potentially nonconvex, constraints has been a fruitful direction of research for computational mixed integer nonlinear programs (MINLPs) in the last decade. In this paper, we follow that path in order to extend another essential subroutine of modern MIP solvers toward the case of nonlinear optimization: the analysis of infeasible subproblems for learning additional valid constraints. To this end, we derive two different strategies, geared toward two different solution approaches. These are using local dual pro

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25

Bartali, Lorenzo, Marco Gabiccini, and Massimo Guiggiani. "A Pnh-adaptive Refinement Procedure for Numerical Optimal Control Problems." Journal of Computational and Nonlinear Dynamics, March 30, 2023, 1–30. http://dx.doi.org/10.1115/1.4062227.

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Abstract This paper presents an automatic procedure to enhance the accuracy of the numerical solution of an optimal control problem (OCP) discretized via direct collocation at Gauss-Legendre points. First, a numerical solution is obtained by solving a nonlinear program (NLP). Then, the method evaluates its accuracy and adaptively changes both the degree of the approximating polynomial within each mesh interval and the number of mesh intervals until a prescribed accuracy is met. The number of mesh intervals is increased for all state vector components alike, in a classical fashion. Instead, imp

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26

Guo, Zhong, Aditya Chaudhari, Austin R. Coffman, and Prabir Barooah. "Optimal Control of District Cooling Energy Plant With Reinforcement Learning and MPC." ASME Journal of Engineering for Sustainable Buildings and Cities, November 7, 2023, 1–16. http://dx.doi.org/10.1115/1.4064023.

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Abstract We consider the problem of optimal control of district cooling energy plants (DCEPs) consisting of multiple chillers, a cooling tower, and a thermal energy storage (TES), in the presence of time-varying electricity price. A straightforward application of model predictive control (MPC) requires solving a challenging mixed-integer nonlinear program (MINLP) because of the on/off of chillers and the complexity of the DCEP model. Reinforcement learning (RL) is an attractive alternative since its real-time control computation is much simpler. But designing an RL controller is challenging du

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27

Azmi, Ashraf, Suhairi Abdul Sata, Fakhrony Sholahudin Rohman, and Norashid Aziz. "Optimization studies of low-density polyethylene process: effect of different interval numbers." Chemical Product and Process Modeling, June 1, 2020. http://dx.doi.org/10.1515/cppm-2019-0125.

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AbstractThe highly exothermic nature of the low-density polyethylene (LDPE) polymerization process and the heating-cooling prerequisite in tubular reactor can lead to various problems particularly safety and economic. These issues complicate the monomer conversion maximization approaches. Consequently, the dynamic optimization study to obtain maximum conversion of the LDPE is carried out. A mathematical model has been developed and validated using industrial data. In the dynamic optimization study, maximum monomer conversion (XM) is considered as the objective function, whereas the constraint

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28

Rodriguez, Jose S., Robert B. Parker, Carl D. Laird, Bethany L. Nicholson, John D. Siirola, and Michael L. Bynum. "Scalable Parallel Nonlinear Optimization with PyNumero and Parapint." INFORMS Journal on Computing, March 15, 2023. http://dx.doi.org/10.1287/ijoc.2023.1272.

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We describe PyNumero, an open-source, object-oriented programming framework in Python that supports rapid development of performant parallel algorithms for structured nonlinear programming problems (NLP’s) using the Message Passing Interface (MPI). PyNumero provides three fundamental building blocks for developing NLP algorithms: a fast interface for calculating first and second derivatives with the AMPL Solver Library (ASL), a number of interfaces to efficient linear solvers, and block-structured vectors and matrices based on NumPy, SciPy, and MPI that support distributed parallel storage and

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29

Prof., Vyankatesh S. Kulkarni. "Development of Matlab Programme to study nonlinear vibration of a cantilever beam." IJIERT - International Journal of Innovations in Engineering Research and Technology 2, no. 5 (2015). https://doi.org/10.5281/zenodo.1471198.

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<strong><strong> </strong>The finite element model for the nonlinear transverse vibration of t he beam was implemented in the program NLB This program was used to calculate the steady state response of the beam. The numerical results from the program were compared to the experimental res ults obtained by Malatkar (2003). The NLB program was also used to calculate the transient response of the be am,which was compared with the response obtained with ANSYS. The paper is a extension of the research papers which has been publishe d earlier in this issue of journal and December 2014 issue.</st

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30

Tangaramvong, S., F. Tin-Loi, C. M. Song, and W. Gao. "Interval Limit Analysis Within a Scaled Boundary Element Framework." ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg 1, no. 4 (2015). http://dx.doi.org/10.1115/1.4030471.

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The paper proposes a novel approach for the interval limit analysis of rigid-perfectly plastic structures with (nonprobabilistic) uncertain but bounded forces and yield capacities that vary within given continuous ranges. The discrete model is constructed within a polygon-scaled boundary finite element framework, which advantageously provides coarse mesh accuracy even in the presence of stress singularities and complex geometry. The interval analysis proposed is based on a so-called convex model for the direct determination of both maximum and minimum collapse load limits of the structures inv

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31

Xiaofeng, Tang. "Ecological driving on multiphase trajectories and multiobjective optimization for autonomous electric vehicle platoon." Scientific Reports 12, no. 1 (2022). http://dx.doi.org/10.1038/s41598-022-09156-2.

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AbstractAutonomous electric vehicles promise to improve traffic safety, increase fuel efficiency and reduce congestion in future intelligent transportation systems. Ecological driving characteristics are first studied to concentrate on energy consumption, the ability to quickly pass its destination, etc. of autonomous electric vehicle plans (AEVPs) to maximize total energy efficiency benefits. To realize this goal, an optimal control model is developed to provide ecological driving suggestions to AEVPs. The Radau pseudospectral method (RPM) is adopted to put the optimal control model into nonl

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Bi-Huei, Tsai. "Forecasting Foreign Direct Investment with Modified Diffusion Model." May 27, 2010. https://doi.org/10.5281/zenodo.1061100.

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Prior research has not effectively investigated how the profitability of Chinese branches affect FDIs in China [1, 2], so this study for the first time incorporates realistic earnings information to systematically investigate effects of innovation, imitation, and profit factors of FDI diffusions from Taiwan to China. Our nonlinear least square (NLS) model, which incorporates earnings factors, forms a nonlinear ordinary differential equation (ODE) in numerical simulation programs. The model parameters are obtained through a genetic algorithms (GA) technique and then optimized with the collected

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Bartali, L., E. Grabovic, and M. Gabiccini. "A consensus-based alternating direction method of multipliers approach to parallelize large-scale minimum-lap-time problems." Multibody System Dynamics, October 6, 2023. http://dx.doi.org/10.1007/s11044-023-09932-6.

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AbstractMinimum-lap-time planning (MLTP) problems, which entail finding optimal trajectories for race cars on racetracks, have received significant attention in the recent literature. They are commonly addressed as optimal control problems (OCPs) and are numerically discretized using direct collocation methods. Subsequently, they are solved as nonlinear programs (NLPs). The conventional approach to solving MLTP problems is serial, whereby the resulting NLP is solved all at once. However, for problems characterized by a large number of variables, distributed optimization algorithms, such as the

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