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Optimal vaccination and control strategies against dengue

MATHEMATICAL METHODS IN THE APPLIED SCIENCES 2019年第10期42卷 3496-3507页

作者： Fischer, Anne Chudej, Kurt Pesch, Hans Josef Univ Bayreuth Lehrstuhl Ingenieurmath Bayreuth Germany Univ Bayreuth Lehrstuhl Wissensch Rechnen D-95440 Bayreuth Germany

This article focuses on the mathematical modelling of a disease outbreak of dengue fever. A cost-efficient fighting strategy, which simultaneously uses vaccination, application of insecticides to adult and aquatic mosquitoes, and an approach to decrease the number of man-made breeding places for the mosquitoes, is computed using optimal control. Vaccination includes a paediatric vaccination and an imperfect random mass vaccination with waning immunity.

关键词： Asian tiger mosquito dengue insecticide non-linear programming optimal control vaccination

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A decision-support system to assist forest industry planning and investment when data are scarce: the case of hardwood veneering in subtropical eastern Australia

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AUSTRALIAN FORESTRY 2021年第2期84卷 59-72页

作者： Venn, T. J. McGavin, R. L. Univ Queensland Fac Sci Sch Agr & Food Sci St Lucia Qld 4072 Australia Queensland Govt Dept Agr & Fisheries Agrisci Queensland Salisbury SA Australia Univ Queensland Sch Civil Engn Fac Engn Architecture & Informat Technol St Lucia Qld Australia

An aspatial mathematical model has been developed to simultaneously support log processing investment decisions with respect to processing scale, facility location and log procurement when data are scarce. A key design principle was to make the model suitable for use by industry. The objective function maximises gross margins per hour of log processing time, and the model accounts for potential processing efficiencies with larger-diameter logs. To support log procurement decisions, the model estimates mill-delivered log costs at which a log procurement officer should be indifferent between purchasing alternative log types. The utility of the model is demonstrated with an application to rotary veneer processing of hardwood logs in subtropical eastern Australia. Complex interactions between processing scale, facility location and log procurement strategies were revealed by substantial differences in gross margins between modelled scenarios. Log procurement decisions were found to have the greatest potential impact on gross margins, followed by facility location and processing scale. The model highlighted that substantially higher returns can be earned from optimal log procurement strategies relative to approaches that either minimise log costs, maximise product recovery or do not differentiate between log types and simply utilise all available log volume.

关键词： operations research non-linear programming processing scale facility location log procurement rotary veneer financial performance

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MINLP Optimization of a Single-Storey Industrial Steel Building

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STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING 2008年第10期54卷 707-724页

作者： Zula, Tomaz Kravanja, Zdravko Kravanja, Stojan Univ Maribor Fac Civil Engn SLO-2000 Maribor Slovenia Univ Maribor Fac Chem & Chem Engn SLO-2000 Maribor Slovenia

The paper presents the topology and standard sizes optimization of a single-storey industrial steel building, made from standard hot rolled I sections. The structure consists of main portal frames, connected with purlins. The structural optimization is performed by the Mixed-Integer non-linear programming approach (MINLP). The MINLP performs a discrete topology and standard dimension optimization simultaneously with continuous parameters. Since the discrete/continuous optimization problem of the industrial building is non-convex and highly non-linear, the Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm has been used for the optimization. Alongside the optimum structure mass, the optimum topology with the optimum number of portal frames and purlins as well as all standard cross-section sizes have been obtained. The paper includes the theoretical basis and a practical example with the results of the optimization. (C) 2008 Journal of Mechanical Engineering. All rights reserved.

关键词： industrial buildings topology optimization sizing optimization non-linear programming MINLP

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An adaptive conic trust-region method for unconstrained optimization

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OPTIMIZATION METHODS & SOFTWARE 2005年第6期20卷 665-677页

作者： Han, QM Sun, WY Han, JY Sampaio, RJB Nanjing Normal Univ Sch Math & Comp Sci Nanjing 210097 Peoples R China Chinese Acad Sci Inst Appl Math Beijing 100080 Peoples R China Pontificia Univ Catolica Parana Grad Program Prod & Syst Engn BR-81611970 Curitiba Parana Brazil

It is well known that among the current methods for unconstrained optimization problems the quasi-Newton methods with global strategy may be the most efficient methods, which have local superlinear convergence. However, when the iterative point is far away from the solution of the problem, quasi-Newton method may proceed slowly for the general unconstrained optimization problems. In this article an adaptive conic trust-region method for unconstrained optimization is presented. Not only the gradient information but also the values of the objective function are used to construct the local model at the current iterative point. Moreover, we define a concept of super steepest descent direction and embed its information into the local model. The amount of computation in each iteration of this adaptive algorithm is the same as that of the standard quasi-Newton method with trust region. Some numerical results show that the modified method requires fewer iterations than the standard methods to reach the solution of the optimization problem. Global and local convergence of the method is also analyzed.

关键词： trust-region method conic model Quasi-Newton method non-linear programming self-adjust strategy

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Controlled Islanding Based on the Coherency of Generators and Minimum Electrical Distance

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IEEE ACCESS 2021年 9卷 146830-146840页

作者： Aghamohammadi, M. R. Mahdavizadeh, S. Fazel Shahid Beheshti Univ Elect Engn Dept Tehran *** Iran

Inter-area oscillations and cascading failures are the most serious threats to the security of the electric power system. Uncontrolled islanding will occur in the event of an unstable inter-area oscillation or a progressive cascading failure. The establishment of uncontrolled islands with a deficiency in load-generation balance is the main reason for system blackout. Controlled islanding has been proposed as a preventive strategy for reducing the risk of blackout in this regard. A new algorithm for applying the controlled islanding strategy is proposed in this paper, based on load coherency and nearest electrical distances between coherent groups of generators. Coherent generators as the main core for controlled islands are identified in this method, which is based on the correlation coefficients between generators and the DBSCAN clustering algorithm. The sub-networks are then created by applying mixed-integer linear programming to each coherent group. Once this is accomplished, non-linear programming is used to construct the stable sub-networks associated with islands that meet the requirements of load-generation balance, voltage limitations, and transmission limits. The proposed scheme is implemented on the small-scale IEEE 39-bus system and a large-scale realistic power system which is the Iran power grid. The results demonstrate that the proposed method is capable of being implemented in a real power system.

关键词： Intentional islanding generator coherency electrical distances DBSCAN algorithm Dijkstra algorithm non-linear programming

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A general non-linear optimization algorithm for lower bound limit analysis

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INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING 2003年第2期56卷 165-184页

作者： Krabbenhoft, K Damkilde, L Tech Univ Denmark Dept Civil Engn DK-2800 Lyngby Denmark

The non-linear programming problem associated with the discrete lower bound limit analysis problem is treated by means of an algorithm where the need to linearize the yield criteria is avoided. The algorithm is an interior point method and is completely general in the sense that no particular finite element discretization or yield criterion is required. As with interior point methods for linear programming the number of iterations is affected only little by the problem size. Some practical implementation issues are discussed with reference to the special structure of the common lower bound load optimization problem. and finally the efficiency and accuracy of the method is demonstrated by means of examples of plate and slab structures obeying different non-linear yield criteria. Copyright (C) 2002 John Wiley Sons. Ltd.

关键词： limit analysis finite element method lower bound method non-linear programming

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Convexification method for bilinear transmission expansion problem

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2014年第5期24卷 638-652页

作者： Cedeno, Enrique B. Arora, Sant Univ Minnesota Ind & Syst Engn Dept Minneapolis MN 55455 USA

This research presents a method for convexifying the non-linear constraints and the objective function for the Transmission Network Expansion Planning Problem (TNEP). The TNEP seeks to identify the best set of transmission capacity additions to meet a future electric power demand. The TNEP is a non-convex Mixed Integer non-linear programming problem for which a variety of primal solution methods have been designed. In this paper, the TNEP is formulated as a bilinear programming problem subject to bilinear constraints. This allows resolving the non-linearities through convexification of the non-linear objective function and the constraints for a relaxation of the TNEP in which integrality requirements are removed. The final solution for the original TNEP problem is obtained by using a branch and bound strategy. It was found by using a two-node test case that the convexification method presented in this paper in conjunction with a brand and bound strategy identifies the optimal solution. Successfully solving a small-scale test problem through convexification presents a promising scenario to solve larger scale problems. This primal-dual method allows identifying the duality gap which is a limitation of primal methods. Further multidisciplinary research is needed to extend the method presented here to larger cases and real life networks. Copyright (c) 2013 John Wiley & Sons, Ltd.

关键词： bilinear programming non-linear programming convexification transmission planning

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A fast decoupling capacitor budgeting algorithm for robust on-chip power delivery

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2004年第12期E87A卷 3273-3280页

作者： Fu, JJ Luo, ZY Hong, XL Cai, YC Tan, SXD Pan, Z Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China Univ Calif Riverside Dept Elect Engn Riverside CA 92521 USA

In this paper, we present an efficient method to budget onchip decoupling capacitors (decaps) to optimize power delivery networks in an area efficient way. Our algorithm is based on an efficient gradient-based non-linear programming method for searching the solution. Our contributions are an efficient gradient computation method (time-domain merged adjoint network method) and a novel equivalent circuit modeling technique to speed up the optimization process. Experimental results demonstrate that the algorithm is capable of efficiently optimizing very large scale P/G networks.

关键词： power delivery optimization decoupling capacitor non-linear programming

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Demand Response Model Development for Smart Households Using Time of Use Tariffs and Optimal Control-The Isle of Wight Energy Autonomous Community Case Study

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ENERGIES 2020年第3期13卷

作者： Khanna, Sourav Becerra, Victor Allahham, Adib Giaouris, Damian Foster, Jamie M. Roberts, Keiron Hutchinson, David Fawcett, Jim Univ Portsmouth Sch Energy & Elect Engn Portsmouth PO1 3DJ Hants England Newcastle Univ Sch Engn Newcastle Upon Tyne NE1 7RU Tyne & Wear England Univ Portsmouth Sch Math & Phys Portsmouth PO1 2UP Hants England Univ Portsmouth Fac Technol Portsmouth PO1 3AH Hants England Isle Wight Council Cty Hall Newport PO30 1UD Isle Of Wight England

Residential variable energy price schemes can be made more effective with the use of a demand response (DR) strategy along with smart appliances. Using DR, the electricity bill of participating customers/households can be minimised, while pursuing other aims such as demand-shifting and maximising consumption of locally generated renewable-electricity. In this article, a two-stage optimization method is used to implement a price-based implicit DR scheme. The model considers a range of novel smart devices/technologies/schemes, connected to smart-meters and a local DR-Controller. A case study with various decarbonisation scenarios is used to analyse the effects of deploying the proposed DR-scheme in households located in the west area of the Isle of Wight (Southern United Kingdom). There are approximately 15,000 households, of which 3000 are not connected to the gas-network. Using a distribution network model along with a load flow software-tool, the secondary voltages and apparent-power through transformers at the relevant substations are computed. The results show that in summer, participating households could export up to 6.4 MW of power, which is 10% of installed large-scale photovoltaics (PV) capacity on the island. Average carbon dioxide equivalent (CO(2)e) reductions of 7.1 ktons/annum and a reduction in combined energy/transport fuel-bills of 60%/annum could be achieved by participating households.

关键词： demand response electric vehicle solar photovoltaics battery optimisation non-linear programming sustainability

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Random derivative-free algorithm for solving unconstrained or bound constrained continuously differentiable non-linear problems

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OPTIMIZATION METHODS & SOFTWARE 2015年第5期30卷 911-933页

作者： Jaberipour, Majid Khorram, Esmaile Karimi, Behrooz Amirkabir Univ Technol Dept Appl Math Fac Math & Comp Sci Tehran 15914 Iran Amirkabir Univ Technol Dept Ind Engn Tehran 15914 Iran

Derivative-free optimization is an area of long history which has so many applications in different fields. It has lately received considerable attention within the engineering community. This paper describes a random derivative-free algorithm for solving unconstrained or bound constrained continuously differentiable non-linear problems. This method is a combination of particle swarm and directional direct search algorithms. The key difference in direct search methods is in the way of generating positive bases. At first glance, a simple way of generating positive bases has been introduced for solving continuously differentiable problems. Then, it has been shown that using the particle swarm algorithm with a direct search algorithm can solve non-linear optimization problems efficiently. Some standard examples have been presented to demonstrate the ability and effectiveness of this approach.

关键词： particle swarm derivative-free unconstrained problems bound constrained problems non-linear programming

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