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non-linear programming in shakedown analysis with plasticity and friction

JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS 2017年 104卷 71-83页

作者： Spagnoli, A. Terzano, M. Barber, J. R. Klarbring, A. Univ Parma Dept Engn & Architecture Viale Usberti 181-A I-43124 Parma Italy Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA Linkoping Univ Dept Mech Engn S-58183 Linkoping Sweden

Complete frictional contacts, when subjected to cyclic loading, may sometimes develop a favourable situation where slip ceases after a few cycles, an occurrence commonly known as frictional shakedown. Its resemblance to shakedown in plasticity has prompted scholars to apply direct methods, derived from the classical theorems of limit analysis, in order to assess a safe limit to the external loads applied on the system. In circumstances where zones of plastic deformation develop in the material (e.g., because of the large stress concentrations near the sharp edges of a complete contact), it is reasonable to expect an effect of mutual interaction of frictional slip and plastic strains on the load limit below which the global behaviour is non dissipative, i.e., both slip and plastic strains go to zero after some dissipative load cycles. In this paper, shakedown of general two-dimensional discrete systems, involving both friction and plasticity, is discussed and the shakedown limit load is calculated using a non-linear programming algorithm based on the static theorem of limit analysis. An illustrative example related to an elastic-plastic solid containing a frictional crack is provided. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Limit analysis Shakedown Complete contact Friction non-linear programming

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non-linear programming for the optimization of machine repair problems in fuzzy environments

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ENGINEERING OPTIMIZATION 2006年第7期38卷 789-799页

作者： Chen, Shih-Pin Natl Chung Cheng Univ Dept Business Adm Chiayi 621 Taiwan

Machine repair models have wide applications in many systems such as production line systems and maintenance operations. A procedure is developed to derive the fuzzy objective value of the cost-based machine repair optimization problem, in that the cost coefficients and the machine breakdown rate are fuzzy numbers. On the basis of the extension principle, a pair of non-linear programs are formulated to calculate the lower and upper bounds of the fuzzy minimum expected total cost at the possibility level alpha. The membership function of the minimum expected total cost is constructed by enumerating different values of alpha. A numerical example is solved successfully to demonstrate the validity of the proposed method. Since the minimum expected total cost is completely expressed by a membership function rather than by a crisp value, the fuzziness of the input data is conserved, and more information is provided for decision-making. Furthermore, since the optimum repair rate obtained is fuzzy, a crisp optimum repair rate based on the Yager ranking indices is recommended for practical use.

关键词： machine repair machine interference fuzzy sets non-linear programming

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non-linear programming Method for Buffer Allocation in Unreliable Production Lines

Non-linear Programming Method for Buffer Allocation in Unrel...

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21st International Conference on Analytical and Stochastic Modelling Techniques and Applications (ASMTA)

作者： Ouazene, Yassine Yalaoui, Alice Yalaoui, Farouk Chehade, Hicham Univ Technol Troyes Inst Charles Delaunay Lab Optimisat Syst Ind UMR CNRS 6281 F-10004 Troyes France

ISBN: (纸本)9783319082196;9783319082189

This paper proposes a new algorithm based on a non-linear programming approach to deal with the buffer allocation problem in the case of unreliable production lines. Processing, failure and repair times are assumed to be random variables exponentially distributed. The proposed approach can be used to solve the different versions of the buffer allocation problem: primal, dual and generalized. This method is based on the modeling and the analysis of the serial production line using an equivalent machines method. The idea is to model the different possible states of each buffer using dedicated birth-death Markov processes to calculate the blockage and starvation probabilities of each machine. Then, each original machine is replaced by an equivalent one taking into account these probabilities. A comparative study based on different test instances issued from the literature is presented and discussed. The obtained results show the effectiveness and the accuracy of the proposed approach.

关键词： Buffer allocation Unreliable production lines Equivalent Machine Method non-linear programming Birth-death processes

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Constrained non-linear programming: A minimum cross-entropy algorithm

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ENGINEERING OPTIMIZATION 1999年第4期31卷 479-487页

作者： Das, NC Mazumder, SK De, K Bengal Engn Coll DU Dept Math Howrah 711103 W Bengal India Univ Calcutta Dept Math Kolkata 700073 W Bengal India Vidyasagar Univ Dept Math Midnapore W Bengal India

The paper presents an information-theoretic algorithm for solving constrained non-linear programming problems based upon the principle of minimum cross-entropy and surrogate mathematical programming. It is an alternative to the earlier work by Templeman and Li [4-6] based on the maximum entropy principle and so far as the rate of convergence of the solution is concerned it is an improvement upon it. The merit of the present technique is illustrated with two numerical examples.

关键词： entropy cross-entropy non-linear programming surrogate constraints minimum-cross entropy principle

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Transmission-expansion planning based on a non-linear programming algorithm

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APPLIED ENERGY 2003年第1-3期76卷 169-177页

作者： Al-Hamouz, ZM Al-Faraj, AS King Fahd Univ Petr & Minerals Dept Elect Engn Dhahran 31261 Saudi Arabia

In this formulation, the objective function and operating constraints include the corona power-loss term. The objective function consists of three terms: cost of investment of new transmission lines, ohmic power loss of new and existing lines, and corona-power loss of new lines. This combination of terms results in a non-linear objective function. The non-linear programming or the non-convex optimization technique is used to solve such large-scale practical problem. The new formulation has been applied to the 28-bus Jordanian high-voltage transmission network in order to test and justify its applicability. (C) 2003 Elsevier Ltd. All rights reserved.

关键词： corona power loss expansion non-linear programming planning transmission lines

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Adaptive mesh-free lower bound limit analysis using non-linear programming

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SCIENTIA IRANICA 2017年第6期24卷 2793-2802页

作者： Binesh, S. M. Rasekh, S. Shiraz Univ Technol Dept Civil & Environm Engn Shiraz Iran

An adaptive mesh-free approach is developed to compute the lower bounds of limit loads in plane strain soil mechanics problems. There is no pre-defined connectivity between nodes in the mesh-free techniques, and this property facilitates the implementation of h-adaptivity. Nodes may be added, moved, or discarded without complex changes in the data structures involved. In this regard, the Shepard mesh-free method is used in conjunction with the nodal stress rate smoothing technique and the lower bound limit analysis theory to establish a non-linear optimization problem. This problem is solved by the second-order cone programming technique, and the result is a stress field that satisfies the lower bound requirements in a non-rigorous manner. The lack of rigorousness arises from relaxation during nodal stress rate smoothing process. An error estimator is introduced by the application of Taylor series expansion, and by controlling the local error via a user-de fined tolerance, the adaptive refinement strategy is established. To demonstrate the effectiveness of the proposed method, the procedure is applied to the examples of purely cohesive and cohesive-frictional soils. (C) 2017 Sharif University of Technology. All rights reserved.

关键词： Adaptive Mesh-free Lower bound non-linear programming Plane strain

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Investigating the Utility of Water Cycle Optimization and non-linear programming Techniques in Electric Vehicle Stations Smart Planning

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IETE JOURNAL OF RESEARCH 2024年第1期70卷 597-609页

作者： Elkasrawy, M. A. Besadap, Peter Makeen Abdullatif, Sameh O. Memon, Saim Ghali, Hani A. British Univ Egypt BUE Fac Engn Ctr Emerging Learning Technol CELT FabLab El Sherouk 11837 Egypt British Univ Egypt BUE Fac Engn Renewable Energy Postgrad Programme El Sherouk 11837 Egypt London South Bank Univ London Ctr Energy Engn Sch Engn Div Elect & Elect Engn London SE1 0AA England Univ Huddersfield Ctr Efficiency & Performance Engn CEPE Sch Comp & Engn Dept Engn & Technol Huddersfield HD1 3DH W Yorkshire England

Transportation electrification shows enormous prospects regarding the global environmental pollution issue. However, the penetration of electric vehicles (EVs) is not massive in the global market. We attribute this to the long AC charging time and the limitations of the charging topologies at home. Accordingly, the need for a centralized electrical vehicle station (EVS) becomes a must to enlarge the contribution of the EVs industry market. Intelligent decision-making is essential in enhancing the EVS performance by optimizing the charging time and minimizing the queuing delay, especially during peak hours. In the current study, we propose an entire scenario for an EVS with a maximum of 14 EVs at peak hours. Multiple charging methodologies have been provided, including DC constant current constant voltage, DC multistage constant currents, AC 110/120 V, and AC 220/240 V. In addition, four various photovoltaic/grid integration scenarios have been introduced seeking the optimum EVS operation concerning;Levelized cost of energy, charging time and capacity. Finally, two charging schemes have been demonstrated, targeting a minimum total charging time and queuing delay, where the water cycle optimization technique has been enrolled in parallel with non-linear programming. A significant reduction in the total charging time, nearly 90%, has been reached concerning the overnight in-home AC charging time.

关键词： Electric vehicles LCOE meta-heuristic optimization non-linear programming photovoltaic system queuing delay optimization

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A non-linear programming-based similarity reasoning scheme for modelling of monotonicity-preserving multi-input fuzzy inference systems

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2012年第2-3期23卷 71-92页

作者： Tay, Kai Meng Jee, Tze Ling Lim, Chee Peng Univ Malaysia Sarawak Dept Elect Engn Fac Engn Kuching Malaysia Univ Sci Malaysia Sch Comp Sci Petaling Jaya Malaysia

In this paper, the zero-order Sugeno Fuzzy Inference System (FIS) that preserves the monotonicity property is studied. The sufficient conditions for the zero-order Sugeno FIS model to satisfy the monotonicity property are exploited as a set of useful governing equations to facilitate the FIS modelling process. The sufficient conditions suggest a fuzzy partition (at the rule antecedent part) and a monotonically-ordered rule base (at the rule consequent part) that can preserve the monotonicity property. The investigation focuses on the use of two Similarity Reasoning (SR)-based methods, i.e., Analogical Reasoning (AR) and Fuzzy Rule Interpolation (FRI), to deduce each conclusion separately. It is shown that AR and FRI may not be a direct solution to modelling of a multi-input FIS model that fulfils the monotonicity property, owing to the difficulty in getting a set of monotonically-ordered conclusions. As such, a non-linear programming (NLP)-based SR scheme for constructing a monotonicity-preserving multi-input FIS model is proposed. In the proposed scheme, AR or FRI is first used to predict the rule conclusion of each observation. Then, a search algorithm is adopted to look for a set of consequents with minimized root means square errors as compared with the predicted conclusions. A constraint imposed by the sufficient conditions is also included in the search process. Applicability of the proposed scheme to undertaking fuzzy Failure Mode and Effect Analysis (FMEA) tasks is demonstrated. The results indicate that the proposed NLP-based SR scheme is useful for preserving the monotonicity property for building a multi-input FIS model with an incomplete rule base.

关键词： Fuzzy inference system similarity reasoning analogical reasoning fuzzy rule interpolation non-linear programming monotonicity property failure mode and effect analysis

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Synthesis of a Radiating Elements for Side Lobe Reduction Using a Hybrid Beamforming Technique Based on non-linear programming and Stochastic Optimization

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TRAITEMENT DU SIGNAL 2022年第3期39卷 771-780页

作者： Brahimi, Mohamed Inc, Mustafa Ahmad, Hijaz Menni, Younes Lorenzini, Giulio Univ Ctr Salhi Ahmed Naama Ctr Univ Naama Dept Technol POB 66 Naama 45000 Algeria Biruni Univ Dept Comp Engn TR-34025 Istanbul Turkey Firat Univ Sci Fac Dept Math TR-23119 Elazig Turkey China Med Univ China Med Univ Hosp Dept Med Res Taichung 40402 Taiwan Int Telemat Univ Uninettuno Sect Math Corso Vittorio Emanuele II 39 I-00186 Rome Italy Univ Parma Dept Engn & Architecture Parco Area Sci 181-A I-43124 Parma Italy

In this article, an algorithm with global constraints known as hybrid non-linear programming with particle swarm enhancement is available for improving the circular antenna array (CAA) radiation characteristics. The suggested method combines the optimization of excitation currents with the array's element spacing to create the correct beam patterns. In this context, adaptive particle optimization (APSO) and basic particle swarm optimization (BPSO) algorithms are applied with the previous method to the (8,12,20) elements to tune the array's amplitude and positioning to achieve a radiation profile with reduced SLL. The simulated results show that the recommended strategy provides the greatest decrease in side lobe levels and directivity.

关键词： non-linear programming stochastic optimization mathematical modeling circular antenna elements side lobe level particle swarm enhancement

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Best proximity point theorems: resolution of an important non-linear programming problem

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OPTIMIZATION LETTERS 2013年第6期7卷 1167-1177页

作者： Basha, S. Sadiq Anna Univ Dept Math Madras 600025 Tamil Nadu India

The purpose of this article is to resolve the non-linear programming problem of globally minimizing the real valued function where S is a non-self-mapping in the setting of a metric space with the distance function 'd'. An iterative algorithm is also furnished to find a solution of such global optimization problems. As a consequence, one can determine an optimal approximate solution to some equations of the form Sx = x.

关键词： Global optimization non-linear programming Optimal approximate solution Best proximity point Fixed point Weak contraction Contraction Proximal contraction Generalized proximal contraction Proximal cyclic contraction Generalized proximal cyclic contraction

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