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A combined approach of the MLPG method and nonlinear programming for lower-bound limit analysis

CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES 2008年第1期28卷 39-55页

作者： Chen, S. S. Liu, Y. H. Cen, Z. Z. Tsinghua Univ Dept Engn Mech Beijing 100084 Peoples R China

In most engineering applications, solutions derived from the lower-bound theorem of plastic limit analysis are particularly valuable because they provide a safe estimate of the load that will cause plastic collapse. A solution procedure based on the meshless local Petrov-Galerkin (MLPG) method is proposed for lower-bound limit analysis. This is the first work for lower-bound limit analysis by this meshless local weak form method. In the construction of trial functions, the natural neighbour interpolation (NNI) is employed to simplify the treatment of the essential boundary conditions. The discretized limit analysis problem is solved numerically with the reduced-basis technique. The self-equilibrium stress field is constructed by a linear combination of several self-equilibrium stress basis vectors, which can be computed by performing an equilibrium iteration procedure during elasto-plastic incremental analysis. The non-linear programming sub-problems are solved directly by the Complex method and the limit load multiplier converges monotonically to the lower-bound of real solution. Several numerical examples are given to verify the accuracy and reliability of the proposed method for lower-bound limit analysis.

关键词： limit analysis MLPG method natural neighbour interpolation self-equilibrium stress non-linear programming

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生鲜农产品物流网络节点布局优化

生鲜农产品物流网络节点布局优化

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第八届全国交通运输领域青年学术会议

作者：杨华龙刘斐斐唐法浙大连海事大学交通运输管理学院辽宁大连116026

为了解决生鲜农产品物流网络布局优化问题,以从产地、预冷站、配送中心到各个需求点的总物流费用最小为目标函数,并结合生鲜农产品时间敏感特征,通过采集腐烂指数经验数据,测算出因腐烂变质造成的物流损失成本,建立了生鲜农产品物流网... 详细信息

为了解决生鲜农产品物流网络布局优化问题,以从产地、预冷站、配送中心到各个需求点的总物流费用最小为目标函数,并结合生鲜农产品时间敏感特征,通过采集腐烂指数经验数据,测算出因腐烂变质造成的物流损失成本,建立了生鲜农产品物流网络布局非线性规划模型,设计了相应的遗传算法.算例验证了模型和算法的有效性.

关键词： Fresh agricultural product logistics Network node Layout non-linear programming Genetic algorithm

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Compressed sensing - A look beyond linear programming

Compressed sensing - A look beyond linear programming

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33rd IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Bergger, Christian R. Reta, Javier Pattipati, Krishna Willett, Peter Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)9781424414833

Recently, significant attention in compressed sensing has been focused on Basis Pursuit, exchanging the cardinality operator with the l(1)-norm, which leads to a linear formulation. Here, we want to look beyond using the l(1)-norm in two ways: investigating non-linear solutions of higher complexity, but closer to the original problem for one, and improving known low complexity solutions based on Matching Pursuit using rollout concepts. Our simulation results concur with previous findings that once x is "sparse enough", many algorithms find the correct solution, but for averagely sparse problems we find that the l(1)-norm often does not converge to the correct solution - in fact being outperformed by Matching Pursuit based algorithms at lower complexity. The non-linear algorithm we suggest has increased complexity, but shows superior performance in this setting.

关键词： compressed sensing sparse estimation non-linear programming rollout

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Operating rules of an irrigation purposes reservoir using multi-objective optimization

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WATER RESOURCES MANAGEMENT 2008年第5期22卷 551-564页

作者： Consoli, Simona Matarazzo, Benedetto Pappalardo, Nello Univ Catania Dept Agr Engn I-95123 Catania Italy Univ Catania Dept Econ & Quantitat Methods I-95129 Catania Italy

A multi-objective optimization technique for the operation of an irrigation reservoir is presented in this paper. The study deals with two different objective functions (OF): the minimization of reservoir release deficit from the irrigation demand (OF1) and the maximization of net benefit by the demand sector (OF2). In the first step, monthly optimization of each individual objective was performed with a deterministic non-linear programming (NLP) algorithm, that gave the lower and upper bounds for the multi-objective analysis. In the second step, multi-objective optimization was performed through the Constraint method that operates by optimising the objective function OF1, while the other (OF2) was constrained to satisfy release strategies generated by the optimization. non-dominated set of release strategies is generated by parametrically varying the bounds of the constraints obtained from the individual optimal solutions. In the third step, the interactive analytical Step method was applied to find the best compromise solution, between the two OFs, by minimizing the distance of each non-dominated solution to an ideal solution that represents the utopian optimum for both OF1 and OF2. Furthermore, the interactive approach allows to improve the performance of the reservoir in terms of compromise irrigation releases, by changing the OF values until the satisfaction of predetermined criteria fixed by the planners and decision makers. The proposed water allocation model was applied to the Pozzillo reservoir operation, that supplies the Catania Plain irrigation area (Eastern Sicily).

关键词： interactive approach multi-objective optimization net benefit non-linear programming reservoir operating rules water deficits

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Sensitivity analysis in optimization and reliability problems

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2008年第12期93卷 1788-1800页

作者： Castillo, Enrique Minguez, Roberto Castillo, Carmen Univ Cantabria Dept Appl Math & Computat Sci E-39005 Santander Spain Univ Castilla La Mancha Dept Appl Math E-13071 Ciudad Real Spain Univ Castilla La Mancha Dept Civil Engn E-13071 Ciudad Real Spain

The paper starts giving the main results that allow a sensitivity analysis to be performed in a general optimization problem, including sensitivities of the objective function, the primal and the dual variables with respect to data. In particular, general results are given for non-linear programming, and closed formulas for linear programming problems are supplied. Next, the methods are applied to a collection of civil engineering reliability problems, which includes a bridge crane, a retaining wall and a composite breakwater. Finally, the sensitivity analysis formulas are extended to calculus of variations problems and a slope stability problem is used to illustrate the methods. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： Failure modes non-linear programming Optimization, Probabilistic models Reliability analysis Safety factors Sensitivity analysis Bridge crane design Retaining wall Composite breakwaters Calculus of variations Slope stability

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Allocation of long-term financial transmission rights for transmission expansion

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2008年第3期184卷 1122-1139页

作者： Kristiansen, Tarjei Statkraft Energi AS N-0216 Oslo Norway

Long-term financial transmission rights (FTRs) could be used to create incentives for small-scale transmission investments. However, these new investments may cause negative externalities on existing FTRs. Therefore the system operator needs a protocol for awarding incremental FTRs for new transmission capacity that maximize investors' preferences while simultaneously accounting for under-allocation of the existing network capacity by existing FTRs. To preserve revenue adequacy, the system operator calculates a minimum amount of currently unallocated FTRs (or proxy FTRs) that satisfies the power flow constraints in the existing network. The challenge is to define the proxy awards. Hogan proposes to define them as the best use of the current network along the same direction as the incremental FTR awards. This includes allowing positive or negative incremental FTR awards. In this paper we present an implementation through bi-level programming of Hogan's proposal for allocation of long-term FTRs and apply it to a radial line and one of Hogan's examples. Our results show that the simultaneous feasibility of the transmission investment depends on factors such as investor and preset proxy preferences, existing FTRs, and transmission capacity in both the existing network and all proposed expansions of it. (C) 2006 Elsevier B.V. All rights reserved.

关键词： risk management energy non-linear programming finance

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Two-stage time minimizing assignment problem

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2008年第5期36卷 730-740页

作者： Sonia Puri, M. C. Indian Inst Management Decis Sci Grp Lucknow 226013 Uttar Pradesh India Indian Inst Technol Dept Math New Delhi 110016 India

This paper deals with the optimal selection of in out of n facilities to first perform in given primary jobs in Stage-1 followed by the remaining (n - m) facilities performing optimally the (n - m) secondary jobs in Stage-II. It is assumed that in both the stages facilities perform in parallel. The aim of the proposed study is to find that set of in facilities performing the primary jobs in Stage-I for which the sum of the overall completion times of jobs in Stage-I and the corresponding optimal completion time of the secondary jobs in Stage-II by the remaining (n - m) facilities is the minimum. The developed solution methodology involves solving the standard time minimizing and cost minimizing assignment problems alternately after forbidding some facility-job pairings and suggests a polynomially bound algorithm. This proposed algorithm has been implemented and tested on a variety of test problems and its performance is found to be quite satisfactory. (C) 2006 Elsevier Ltd. All rights reserved.

关键词： combinatorial analysis mathematical programming non-linear programming allocation

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The optimal allocating pumping rate of a multi-well system for a brackish water desalination plant

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DESALINATION 2008年第1-3期221卷 215-224页

作者： Hsui, Che-Yu Nanhua Univ Grad Inst Management Sci Chiayi 622 Taiwan

I applied perspectives on operations research (OR) to propose a non-linear mathematical model, termed the APWs (allocation of pumping wells) model, to address problems associated with allocating pumping rates of a multi-well system for a brackish water reverse osmosis (BWRO) plant. In some and and inshore regions, feed water mostly preferred to exploit groundwater, owing to its easier desalted characteristic than seawater. However, the operations of most multi-well systems are always arbitrary, and we could not guarantee the strategies of operation might be optimal;additionally, the pumping quantity and quality variation of each well would all induce the unstable quality of feed water, and then lead to the problem of scaling. Though adding acid could treat the problem of scaling, the acidification, on the other hand, means the increasing cost and damage risk of a reverse osmosis (RO) system. Therefore, the overriding objective of this study is to decide the optimal allocating pumping rate among wells for a RO system on the premise of no acid added and under finite groundwater resources, to ensure feed water has no scaling potential and achieve marginal usage of groundwater resources. The APWs model tries to integrate engineering and management aspects to replace subjective operation of a multi-well system. Here, I apply scaling intensity (SI) proposed by literature that considered calcium carbonate (CaCO3), calcium sulfate (CaSO4) and silica (SiO2) as mainly potential scaling compounds in feed water to assess the scaling potential of a RO system. Besides, I present a solving algorithm for achieving the maximal SI with no scaling occurred. Moreover, I apply the proposed model to a case study in Taiwan by considering four-well system, to obtain optimal allocation with retaining the cleanest residual storage of whole groundwater resources, to avoid the waste of water resources. The results shown that through the assistance of OR technique, it could provide helpful info

关键词： scaling non-linear programming water resources management operations research BWRO

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Optimal control problems with multiple characteristic time points in the objective and constraints

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AUTOMATICA 2008年第11期44卷 2923-2929页

作者： Loxton, R. C. Teo, K. L. Rehbock, V. Curtin Univ Technol Dept Math & Stat Perth WA 6845 Australia

In this paper, we develop a computational method for a class of optimal control problems where the objective and constraint functionals depend on two or more discrete time points. These time points can be either fixed or variable. Using the control parametrization technique and a time scaling transformation, this type of optimal control problem is approximated by a sequence of approximate optimal parameter selection problems. Each of these approximate problems can be viewed as a finite dimensional optimization problem. New gradient formulae for the cost and constraint functions are derived. With these gradient formulae, standard gradient-based optimization methods can be applied to solve each approximate optimal parameter selection problem. For illustration, two numerical examples are solved. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： Control parametrization Optimal control computation non-linear optimal control Constrained optimal control non-linear programming

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To be fair or efficient or a bit of both

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COMPUTERS & OPERATIONS RESEARCH 2008年第12期35卷 3787-3806页

作者： Zukerman, Moshe Mammadov, Musa Tan, Liansheng Ouveysi, Iradj Andrew, Lachlan L. H. Univ Melbourne Dept Elect & Elect Engn ARC Special Res Ctr Ultra Broadband Informat Netw Melbourne Vic 3010 Australia Univ Ballarat Sch Informat Technol & Math Sci Ballarat Vic 3353 Australia Cent China Normal Univ Dept Comp Sci Wuhan 430079 Peoples R China CALTECH Dept Comp Sci Pasadena CA 91125 USA

Introducing a new concept of (alpha, beta)-fairness, which allows for a bounded fairness compromise, so that a source is allocated a rate neither less than 0 = 1, times its fair share, this paper provides a framework ... 详细信息

Introducing a new concept of (alpha, beta)-fairness, which allows for a bounded fairness compromise, so that a source is allocated a rate neither less than 0 <=alpha <= 1, not more than beta >= 1, times its fair share, this paper provides a framework to optimize efficiency (utilization, throughput or revenue) subject to fairness constraints in a general telecommunications network for an arbitrary fairness criterion and cost functions. We formulate a non-linear program (NLP) that finds the optimal bandwidth allocation by maximizing efficiency subject to (alpha, beta)-fairness constraints. This leads to what we call an efficiency-faimess function, which shows the benefit in efficiency as a function of the extent to which fairness is compromised. To solve the NLP we use two algorithms. The first is a well-known branch-and-bound-based algorithm called Lipschitz Global Optimization and the second is a recently developed algorithm called Algorithm for Global Optimization Problems (AGOP). We demonstrate the applicability of the framework to a range of examples from sharing a single link to efficiency fairness issues associated with serving customers in remote communities.(c) 2007 Elsevier Ltd. All rights reserved.

关键词： non-linear programming utility optimization fairness efficiency-fairness tradeoff bandwidth allocation

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