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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 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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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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Lower bound shakedown analysis by using the element free Galerkin method and non-linear programming

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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2008年第45-48期197卷 3911-3921页

作者： Chen, Shenshen Liu, Yinghua Cen, Zhangzhi Tsinghua Univ Dept Engn Mech Beijing 100084 Peoples R China

Shakedown analysis is a powerful tool for assessing the safety of structures under variable repeated loads. By using the element free Galerkin (EFG) method and non-linear programming, a novel numerical solution procedure is developed to perform lower bound shakedown analysis of structures made up of elastoperfectly plastic material. The numerical implementation is very simple and convenient because it is only necessary to construct an array of nodes in the domain under consideration. The reduced-basis technique is adopted here to solve the mathematical programming iteratively in a sequence of reduced self-equilibrium stress subspaces with very low dimensions. The self-equilibrium stress field is expressed by linear combination of several self-equilibrium stress basis vectors with parameters to be determined. These self-equilibrium stress basis vectors are generated by performing an equilibrium iteration procedure during elasto-plastic incremental analysis. The Complex method is used to solve the non-linear programming and determine the lower bound of shakedown load. The proposed numerical method is verified by using several numerical examples and the results show good agreement with other available solutions. (C) 2008 Elsevier B.V. All rights reserved.

关键词： shakedown analysis EFG method self-equilibrium stress reduced-basis technique non-linear programming

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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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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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Hierarchical optimization of district heating plants by integrating evolutionary and non-linear programming algorithms

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APPLIED ENERGY 2024年 373卷

作者： Hassan, Muhammed A. Araji, Mohamad T. Univ Waterloo Sch Architecture 7 Melville St S Cambridge ON N1S 2H4 Canada Cairo Univ Fac Engn Mech Power Engn Dept Giza 12613 Egypt

In district heating systems, the capacity and types of energy sources, along with their control mechanisms to meet heating demands, are intricately linked. Effective planning must consider financial constraints and system operations, especially with thermal storage. Control methods can significantly influence sizing decisions by adjusting heat production and storage rates across different equipment. Addressing these issues concurrently is essential to maximize cost savings throughout the system's lifespan. This study addresses critical research gaps, such as the lack of integrated bi-level schemes that combine evolutionary and mathematical optimizers while maintaining original non-linear problem formulations. Specifically, it puts forward a novel tri-level optimization framework aimed at minimizing the lifecycle cost (LCC) of district heating plants, powered by a mix of green (solar thermal and biomass) and conventional (gas) heat sources, along with daily thermal storage. The three levels of this scheme are: i) a particle swarm optimizer (PSO) to explore capacities of heat production and storage devices to minimize LCC;ii) an interior-point optimizer (Ipopt) to minimize annual operating costs with explicit operational constraints;and iii) a simulation layer to enhance computational efficiency. Technical suggestions regarding the initialization and early termination of Ipopt to achieve the global optimal solution with reasonable computation time are described in detail. When applied to the multi-source plant, this methodology showed successful and rapid convergence of PSO towards feasible system designs. The study achieved a minimum LCC of 36.34 million USD, corresponding to a levelized cost of heat of 0.0256 USD/kWh, by maximizing green heat sources and using moderate-volume storage. Biomass fuel (74.8%) and capital costs of biomass (8.1%) and solar (7.9%) systems were the primary LCC contributors. Thermal storage enhanced operational flexibility;without it, the ga

关键词： District heating Solar energy Biomass Storage tank non-linear programming Particle swarm optimizer

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SL method for computing a near-optimal solution using linear and non-linear programming in cost-based hypothetical reasoning

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KNOWLEDGE-BASED SYSTEMS 2002年第7期15卷 369-376页

作者： Ishizuka, M Matsuo, Y Univ Tokyo Sch Engn Dept Informat & Commun Engn Bunkyo Ku Tokyo 1138656 Japan

Hypothetical reasoning is an important framework for knowledge-based systems, however, its inference time grows exponentially with respect to problem size. In this paper, we present an understandable efficient method called slide-down and lift-up (SL) method which uses a linear programming technique for determining an initial search point and a non-linear programming technique for efficiently finding a near-optimal 0-1 solution. To escape from trapping into local optima, we have developed a new local handler, which systematically fixes a variable to a locally consistent value. Since the behavior of the SL method is illustrated visually, the simple inference mechanism of the method can be easily understood. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： hypothetical reasoning linear programming non-linear programming

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COLLISION AVOIDANCE IN COMMERCIAL AIRCRAFT FREE FLIGHT VIA NEURAL NETWORKS AND non-linear programming

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INTERNATIONAL JOURNAL OF NEURAL SYSTEMS 2008年第5期18卷 371-387页

作者： Christodoulou, Manolis A. Kontogeorgou, Chrysa Tech Univ Crete Dept Elect & Comp Engn Khania 73100 Crete Greece

In recent years there has been a great effort to convert the existing Air Traffic Control system into a novel system known as Free Flight. Free Flight is based on the concept that increasing international airspace capacity will grant more freedom to individual pilots during the enroute flight phase, thereby giving them the opportunity to alter flight paths in real time. Under the current system, pilots must request, then receive permission from air traffic controllers to alter flight paths. Understandably the new system allows pilots to gain the upper hand in air traffic. At the same time, however, this freedom increase pilot responsibility. Pilots face a new challenge in avoiding the traffic shares congested air space. In order to ensure safety, an accurate system, able to predict and prevent conflict among aircraft is essential. There are certain flight maneuvers that exist in order to prevent flight disturbances or collision and these are graded in the following categories: vertical, lateral and airspeed. This work focuses on airspeed maneuvers and tries to introduce a new idea for the control of Free Flight, in three dimensions, using neural networks trained with examples prepared through non-linear programming.

关键词： Free Flight neural networks non-linear programming

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Determination of optimised cut-off grade utilising non-linear programming

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ARABIAN JOURNAL OF GEOSCIENCES 2015年第10期8卷 8963-8967页

作者： Yasrebi, Amir Bijan Wetherelt, Andy Foster, Patrick Kennedy, Gareth Ahangaran, Dariush Kaveh Afzal, Peyman Asadi, Ahmad Univ Exeter Cambome Sch Mines Penryn Cornwall England Islamic Azad Univ Dept Min Engn South Tehran Branch Tehran Iran

One of the most fundamental problems in a mining operation is how to recognise an optimum cut-off grade, which defines the grade for discriminating between ore and waste in an ore body, including ore that is extracted at different periods over a mine life period. Therefore, the identification of an optimised cut-off grade (COG) is a crucial function which has to be monitored during the mine life. The main aim of this study is to propose a modified optimum COG model in order to maximise the profit value (PV) for mining projects. Maximising the PV of a mining operation, which is a non-linear programming, is subject to different constraints involving a general grade distribution within a deposit and three stages of production namely mining, concentrating and refining. The proposed computer-based model is more effective in long-term planning of the open pit mines. To provide a better understanding of the algorithm efficiency, a numerical example is given and subsequently solved based on the Lane algorithm. In order to achieve this, the LINGO software was employed.

关键词： Cut-off grade (COG) Profit value (PV) non-linear programming Lane algorithm

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