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Solution algorithms for regional interactions in large-scale integrated assessment models of climate change

ANNALS OF OPERATIONS RESEARCH 2017年第1-2期255卷 29-45页

作者： Leimbach, Marian Schultes, Anselm Baumstark, Lavinia Giannousakis, Anastasis Luderer, Gunnar Potsdam Inst Climate Impact Res POB 601203 D-14412 Potsdam Germany Tech Univ Berlin Secretariat EB 4-1Str 17 Juni 145 D-10623 Berlin Germany

We present two solution algorithms for a large-scale integrated assessment model of climate change mitigation: the well known Negishi algorithm and a newly developed Nash algorithm. The algorithms are used to calculate the Pareto-optimum and competitive equilibrium, respectively, for the global model that includes trade in a number of goods as an interaction between regions. We demonstrate that in the absence of externalities both algorithms deliver the same solution. The Nash algorithm is computationally much more effective, and scales more favorably with the number of regions. In the presence of externalities between regions the two solutions differ, which we demonstrate by the inclusion of global spillovers from learning-by-doing in the energy sector. The non-cooperative treatment of the spillover externality in the Nash algorithm leads to a delay in the expansion of renewable energy installations compared to the cooperative solution derived using the Negishi algorithm.

关键词： Climate change mitigation General equilibrium non-cooperative solution non-linear programming Trade interaction Energy system modeling

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CSOLNP: Numerical Optimization Engine for Solving non-linearly Constrained Problems

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TWIN RESEARCH AND HUMAN GENETICS 2017年第4期20卷 290-297页

作者： Zahery, Mahsa Maes, Hermine H. Neale, Michael C. Virginia Commonwealth Univ Dept Comp Sci Richmond VA 23284 USA Virginia Commonwealth Univ Dept Psychiat Richmond VA USA

We introduce the optimizer CSOLNP, which is a C++ implementation of the R package RSOLNP (Ghalanos & Theussl, 2012, Rsolnp: General non-linear optimization using augmented Lagrange multiplier method. R package version, 1) alongside some improvements. CSOLNP solves non-linearly constrained optimization problems using a Sequential Quadratic programming (SQP) algorithm. CSOLNP, NPSOL (a very popular implementation of SQP method in FORTRAN (Gill et al., 1986, User's guide for NPSOL (version 4.0): A Fortran package for nonlinear programming (No. SOL-86-2). Stanford, CA: Stanford University Systems Optimization Laboratory), and SLSQP (another SQP implementation available as part of the NLOPT collection (Johnson, 2014, The NLopt nonlinear-optimization package. Retrieved from http://***/nlopt)) are three optimizers available in OpenMx package. These optimizers are compared in terms of runtimes, final objective values, and memory consumption. A Monte Carlo analysis of the performance of the optimizers was performed on ordinal and continuous models with five variables and one or two factors. While the relative difference between the objective values is less than 0.5%, CSOLNP is in general faster than NPSOL and SLSQP for ordinal analysis. As for continuous data, none of the optimizers performs consistently faster than the others. In terms of memory usage, we used Valgrind's heap profiler tool, called Massif, on one-factor threshold models. CSOLNP and NPSOL consume the same amount of memory, while SLSQP uses 71 MB more memory than the other two optimizers.

关键词： OpenMx non-linear programming sequential quadratic programming RSOLNP NPSOL SLSQP

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Generalized memory gradient projection method for non-linear programming with non-linear equality and in-equality constraints

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JOURNAL OF APPLIED MATHEMATICS AND COMPUTING 2011年第1-2期36卷 347-366页

作者： Sun, Qingying Sang, Zhaoyang China Univ Petr Coll Math & Computat Sci Dongying 257061 Shandong Peoples R China

In this paper, generalized gradient projection method is modified to solve non-linear programming with nonlinear equality constraints and in-equality constraints. The global convergence properties of the new method are discussed. Combining quasi-Newton method with our new method, quasi-Newton method is modified to solve non-linear programming with non-linear equality constraints and in-equality constraints. The numerical results illustrate that the new methods are effective.

关键词： non-linear programming Generalized projection non-linear equality constraints and in-equality constraints Memory gradient Convergence

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Selective Maintenance for Complex System with multilevel structure 9

Selective Maintenance for Complex System with multilevel str...

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9th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

作者： Hou Jinxin Qian Yanling Natl Univ Def Technol Coll Informat Syst & Management Changsha 410073 Hunan Peoples R China Natl Univ Def Technol Lab Sci & Technol Integrated Logist Support Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9781509048687

In this paper, we provided a selective maintenance model for complex system with multilevel structure. Our selective maintenance model is so special that we consider the fact when a specific component is maintained so that the subsystems must be removed. We consider that the components have two kind of status, working or failed. We consider three different maintenance actions for the components with different status. The selective maintenance model is formulated as a non-linear programming problem. The objective is to maximum reliability by maintaining part of components of the system in a limited cost. We provided a numerical example to illustrate the effectiveness of the model.

关键词： Selective Maintenance Complex System Multilevel Structure non-linear programming Reliability

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Transport logistics and simulation model for fleet of drones in a Mass Customization System

Transport logistics and simulation model for fleet of drones...

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CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

作者： Olivares, Victor Cordova, Felisa Duran, Claudia Univ Santiago Chile Ind Engn Dept Santiago Chile Univ Finis Terrae Fac Engn Santiago Chile

ISBN: (纸本)9781538631232

This work proposes the use of a fleet of drones (quadcopter/optocopter) inside a production plant of plastic products for the home, in the transport of the materials and components necessary for the personalization of products in the last phases of the production process in a Mass Customization System. A computational tool is designed to configure the fleet to perform certain logistic operations under different operating conditions. It is considered the demand for products (volume and weight), the power and speed of the drones and finally, the distance travelled based on the layout of the plant and transport layout of the drones. The fleet of drones considers a 3D transport space and several structures and configurations have been developed to allow 3D movements. It also analyses the problem of routing of the fleet of drones using several heuristic methods and simulation, whose objective function is to minimize the total cost. An extension of the problem of the traveller seller with capacity and restrictions is analysed (CVRP). Finally, a technological uprising required by the drone transport system is carried out.

关键词： drones Mass Customization non-linear programming optimization vehicle routing problem with capacity and restrictions

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Integer programming techniques for makespan minimizing workforce assignment models that recognize human learning

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COMPUTERS & INDUSTRIAL ENGINEERING 2016年 97卷 202-211页

作者： Jin, Huan Thomas, Barrett W. Hewit, Mike Univ Iowa Tippie Coll Business Dept Management Sci Iowa City IA 52242 USA Loyola Univ Informat Syst & Operat Management Chicago IL 60611 USA

We study optimization techniques for makespan minimizing workforce assignment problems wherein human learning is explicitly modeled. The key challenge in solving these problems is that the learning functions that map experience to worker productivity are usually nonlinear. This paper presents a set of techniques that enable the solution of much larger instances of such problems than seen in the literature to date. The first technique is an exact linear reformulation for the general makespan minimizing workforce assignment models with learning. Next, we introduce a computationally efficient means for generating an initial feasible solution (which our computational experiments indicate is often near optimal). Finally, we present methods for strengthening the formulation with cover inequalities and a lower bound on the objective function value of the optimal solution. With an extensive computational study we demonstrate the value of these techniques and that large instances can be solved much faster than have previously been solved in the literature. To focus the paper on the presented methodology, we solve a makespan minimizing workforce assignment problem that has few complicating constraints. However, the techniques can be adapted to speed up the solution of most any makespan minimizing workforce assignment problem. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Integer programming Learning curves Task assignment Makespan non-linear programming

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Klasické a moderní přístupy k sazbování v neživotním pojištění

Klasické a moderní přístupy k sazbování v neživotním...

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作者： Vojtěch, Jonáš Charles University of Prague

Title: Traditional and modern approaches to pricing in nonlife insurance Abstract: This thesis deals with the theory and implementation of generalized linear models in the area of pricing of non-life insurance and subsequent optimalization of rates. Using the generalized linear models it is possible to estimate expected value and variance of compound distribution of total claims made according to insurance policy during definite time period. The next step is to build an optimalization model and describe several methods how to determine rates that lead to optimal distribution of safety margins within insurance policies in particular risk groups. Represented approaches how to calculate insurance premiums are numerically illustrated on simulated data in concluding parts of the thesis.

关键词： non-life insurance pricing generalized linear model non-linear programming optimal allocation

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Stochastic Technical Losses Analysis of Smart Grids under Uncertain Demand

Stochastic Technical Losses Analysis of Smart Grids under Un...

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International Universities Power Engineering Conference

作者： J-A. Velasco HO_2maris M. Alonso M. Miguelez Electrical Engineering Department Universidad Carlos III de Madrid Gas Natural Fenosa

ISBN: (纸本)9781538629116

Technical losses of smart grids can be computed using the customer's smart meter measurements (active and reactive energy) and the energy measurement registered by the Low Voltage (LV) supervisor deployed at secondary substations. However, in some LV networks, some customers do not provide information regarding the energy consumed and produced in real time. This fact complicates the calculation of technical losses because this information is necessary for estimating the load demand for this subset of customers. In this paper, a stochastic approach is proposed for the estimation of technical losses in smart grids under uncertain load demands (e.g., non-telemetered customers and uncertain smart meters readings). Load demand estimation of non-metered customers was performed by means of a top-down approach. Intra-hour load demand profiles of customers were synthetically generated by applying a Markov process. The data and network used in this process corresponded to the roll-out deployed by the Spanish Research and Development (R&D) demonstration project OSIRIS.

关键词： Markov process non-linear programming Kernel density estimation Advanced metering infrastructure

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Multi-choice stochastic bi-level programming problem in cooperative nature via fuzzy programming approach

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Journal of Industrial Engineering International 2016年第3期12卷 287-298页

作者： Maiti, Sumit Kumar Roy, Sankar Kumar School of Applied Sciences and Humanities Haldia Institute of Technology Purba Midnapore Haldia 721 157 India Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore 721 102 India

In this paper, a Multi-Choice Stochastic Bi-Level programming Problem (MCSBLPP) is considered where all the parameters of constraints are followed by normal distribution. The cost coefficients of the objective functions are multi-choice types. At first, all the probabilistic constraints are transformed into deterministic constraints using stochastic programming approach. Further, a general transformation technique with the help of binary variables is used to transform the multi-choice type cost coefficients of the objective functions of Decision Makers(DMs). Then the transformed problem is considered as a deterministic multi-choice bi-level programming problem. Finally, a numerical example is presented to illustrate the usefulness of the paper. © 2016, The Author(s).

关键词： Bi-level programming Fuzzy programming Multi-choice programming non-linear programming Stochastic programming

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Modelling the mobile target covering problem using flying drones

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OPTIMIZATION LETTERS 2016年第5期10卷 1021-1052页

作者： Pugliese, Luigi Di Puglia Guerriero, Francesca Zorbas, Dimitrios Razafindralambo, Tahiry Univ Calabria Dept Mech Energy & Management Engn I-87036 Arcavacata Di Rende CS Italy Inria Lille Nord Europe Villeneuve Dascq France

This paper addresses the mobile targets covering problem by using unmanned aerial vehicles (UAVs). It is assumed that each UAV has a limited initial energy and the energy consumption is related to the UAV's altitude. Indeed, the higher the altitude, the larger the monitored area and the higher the energy consumption. When an UAV runs out of battery, it is replaced by a new one. The aim is to locate UAVs in order to cover the piece of plane in which the target moves by using a minimum number of UAVs. Each target has to be monitored for each instant time. The problem under consideration is mathematically represented by defining mixed integer non-linear optimization models. Heuristic procedures are defined and they are based on restricted mixed integer programming (MIP) formulation of the problem. A computational study is carried out to assess the behaviour of the proposed models and MIP-based heuristics. A comparison in terms of efficiency and effectiveness among models and heuristics is carried out.

关键词： Targets tracking Unmanned aerial vehicles non-linear programming Matheuristic

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