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International Conference on Smart Energy Systems and Technologies (SEST)

作者： Takada, Koji Ikegami, Takashi Tokyo Univ Agr & Technol Dept Ind Technol & Innovat Tokyo Japan Tokyo Univ Agr & Technol Dept Biofunct & Syst Sci Tokyo Japan

ISBN: (纸本)9781538653265

The use of distributed energy system (DES), such as combined heat and power (CHP) and district heating and cooling system, is spreading. DES is also indispensable for introducing renewable energy. Although introduction cost of renewable energy is high, the generation cost is low. Hence, there is a possibility that marginal fuel cost will be affected an electricity charge. Some external factors can influence on the capacity planning of DES. Therefore, we developed the model to optimize equipment capacities and long-term operations of DES. This planning approach is used two methods, using particle swarm optimization (PSO) and mixed integer linear programming (MILP). The long-term optimization results show that there are changes in the installed capacity and operation.

关键词： distributed energy system combined heat and power long-term optimal operation particle swarm optimization mixed integer linear programming

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Predicting Mode Confusion Through mixed integer linear programming 58

Predicting Mode Confusion Through Mixed Integer Linear Progr...

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58th IEEE Conference on Decision and Control (CDC)

作者： Sivaramakrishnan, Vignesh Thapliyal, Omanshu Vinod, Abraham Oishi, Meeko Hwang, Inseok Univ New Mexico Elect & Comp Engn Albq NM 87131 USA Purdue Univ Aeronaut & Astronaut W Lafayette IN 47907 USA Univ Texas Austin Oden Inst Computat Engn & Sci Austin TX 78712 USA Univ New Mexico Albuquerque NM 87131 USA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113982

Mode confusion, in which the human and the automation have a mismatch in intent, is a contributing factor in many aircraft incidents and accidents. Despite extensive work studying and documenting instances of mode confusion, methodological tools to predict and prevent mode confusion are still lacking. We propose a method to identify mismatches between the pilot and automation intents, in which the pilot intent is inferred from the pilot manual, and the automation intent is an abstraction of the underlying hybrid dynamical system representation of the aircraft and flight management system. We employ a mixed-integer linear programming framework to identify all trajectories from a known initial condition that will result in mismatches in discrete event abstractions which encode both pilot and aircraft intents. We then propose heuristics that use traces from failed trajectories to correct the mode confusion through modifications to the automation intent, via parameterization of guards. We demonstrate our method on the canonical kill-the-capture scenario for longitudinal aircraft dynamics.

关键词： Aircraft Atmospheric modeling Automation Hidden Markov models Discrete-event systems Trajectory mixed integer linear programming

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A multi-period source-sink mixed integer linear programming model for biochar-based carbon sequestration systems

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SUSTAINABLE PRODUCTION AND CONSUMPTION 2016年 8卷 57-63页

作者： Tan, Raymond R. De La Salle Univ Dept Chem Engn 2401 Taft Ave Manila 0922 Philippines

Biochar-based systems are a potentially effective means of large-scale carbon sequestration. Such systems rely on carbonization of biomass into biochar, which can then be added to soil for the dual purpose of sequestering carbon and improving fertility. When properly deployed, these systems can potentially achieve negative emissions through the net transfer of carbon from the atmosphere into the ground. In this work, an optimization model is developed to determine the allocation of biochar streams of different quality levels to various biochar sinks, which are farms whose tolerance to impurities present in biochar are known a priori. The optimization model determines source-sink allocation of biochar so as to minimize total system carbon footprint, while ensuring that soil quality parameters for each sink are not exceeded. An illustrative case study is solved to demonstrate the use of the model.

关键词： Biochar Negative emissions technology Carbon sequestration Optimization mixed integer linear programming Source-sink model

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Spread-Out Bragg Peak in Treatment Planning System by mixed integer linear programming: a Proof of Concept 36

Spread-Out Bragg Peak in Treatment Planning System by Mixed ...

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36th IEEE International Symposium on Computer-Based Medical Systems (CBMS)

作者： Spezialetti, Matteo de Lorenzo, Ramon Gimenez Gravina, Giovanni Luca Placidi, Giuseppe Rossi, Fabrizio Russo, Giorgio Smriglio, Stefano Vittorini, Francesca Mignosi, Filippo Univ Aquila DISIM Dept Laquila Italy San Salvatore Hosp Med Phys Unit ASLI Coppito Abruzzo Italy Univ Aquila DISCAB Dept Laquila Italy Univ Aquila MESVA Dept Laquila Italy Inst Mol Bioimaging & Physiol IBEM CNR Palermo Italy

ISBN: (纸本)9798350312249

In this paper we analyze different mixed integer linear programming (MILP) models in order to produce 1D and 3D Spread-Out Bragg peaks (SOBP) for protons in water. Our techniques do not use much computational resources;in particular, all our experiments have been performed by a standard personal computer. As main result we give the proof of concept that the techniques that we use to create parameterized uniform SOBP can be fruitfully used in Treatment Planning Systems (TPS) for Intensity Modulated Proton Therapy (IMPT). As technical result we show, for the first time to our best knowledge, that there is a trade-off between the minimum number of energies (or layers) to be used to have a SOBP peak within a uniformity tolerance parameter Dt and the same parameter Dt. Minimizing the number of energies also has the advantage of reducing the delivery time using the facilities in operation nowadays.

关键词： Treatment Planning Systems Proton Therapy Computational Resources Spread-out Bragg Peak mixed integer linear programming

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A mixed integer linear programming Method for Generating Backbone Grid 3

A Mixed Integer Linear Programming Method for Generating Bac...

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3rd IEEE International Electrical and Energy Conference (CIEEC)

作者： ZhiYuan, Sun Liu, Mosi Sun, Yan Guangxi Power Grid Co Ltd Elect Power Res Inst Nanning Peoples R China Guangxi Power Grid Co Ltd Power Dispatching & Control Ctr Nanning Peoples R China

ISBN: (纸本)9781728116754

The intelligence algorithm used in the backbone grid search is unrobust and has uncertain results. To tackle the drawback, this paper proposes a mixed integer linear programming (MILP) model for generating the power system backbone grid. Based on the graph theory, this model considers the connectivity of the backbone grid as linear constraints with integer variables. Constrains of line power in the model are elicited by the derivation from Kirchhoff's current law. Since the expressions in this model are analytical and linear, with the help of developed MILP algorithm, the proposed model can fully solve the problem of absence of robustness in existing method. The simulations of IEEE 39-bus system and IEEE 118-bus system show that the proposed model is effective and reliable, which provides a new idea for the development in this research.

关键词： mixed integer linear programming backbone grid Steiner tree connectivity

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An approximate mixed integer linear programming (MILP) model for the design of water reuse/recycle networks with minimum emergy

An approximate mixed integer linear programming (MILP) model...

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11th Asian Pacific Confederation of Chemical Engineering (APCChE)

作者： Tan, R. R. Foo, D. C. Y. Ng, D. K. S. Chiang, C. L. Hu, S. Ku-Pineda, V. De La Salle Univ Dept Chem Engn Manila 1004 Philippines Univ Nottingham Malaysia Sch Chem & Environm Engn Semenyih 43500 Selangor Malaysia Inst Technol Cambodia Chem & Food Technol Dept Phnom Penh Cambodia

Recent trends in process engineering have placed increased emphasis on the design of inherently clean and efficient processes. For example, a wide range of pinch analysis and mathematical programming methods have been developed for designing schemes for water reuse/recycle in industrial plants for both grassroot design and plant retrofit. In the latter case, the conventional approach is to maximize water recovery and thereby minimize fresh water demand and effluent volume. However, it is possible that with such an approach the reductions in environmental impact brought about by saving water can be offset by other impacts arising from increased use of energy and materials in the plant after retrofit. This work presents a model for minimizing the total resource consumption impact of a water reuse/recycle network. The total impact is expressed in terms of emergy - a measure of cumulative solar energy inputs into a life cycle system. A simplified model is proposed that focuses on the impact contributions of water, electrical power and material for capital goods. Two case studies illustrate the approach. Results show that the network with the lowest total impact can be found by sacrificing water recovery for savings in energy and material use. (c) 2007 Curtin University of Technology and John Wiley & Sons, Ltd.

关键词： water reuse/recycle networks mixed integer linear programming life cycle emergy

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Neural Network-based Lyapunov Stability Verification for Continuous-time Nonlinear Systems via mixed integer linear programming 9

Neural Network-based Lyapunov Stability Verification for Con...

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9th International Conference on Control and Robotics Engineering (ICCRE)

作者： Wang, Jingya Yu, Yongbin Wang, Xiangxiang Feng, Xiao Han, Xinyi Cai, Jingye Univ Elect Sci & Technol China Sch Informat & Software Engn Chengdu Peoples R China

ISBN: (纸本)9798350372694;9798350372700

This paper discusses Lyapunov stability verification methods for continuous-time nonlinear systems. Traditional mathematical methods require a lot of manual calculations, which consume a lot of time and energy. To address the problem of the low efficiency in traditional methods, this paper introduces neural networks into the design of the Lyapunov function to achieve independent verification. First, a neural network is used to represent the Lyapunov function. Then, the Lyapunov stability condition is converted into a mixed integer linear programming (MILP) problem, and the solution to the optimization problem is solved through the MILP solver to verify whether the output of the neural network satisfies the Lyapunov stability condition. In addition, this paper gives the training loss function of the Lyapunov neural network, which mainly consists of optimization problems. Finally, a simulation example is given to illustrate the effectiveness of this method.

关键词： neural networks Lyapunov function continuous-time nonlinear systems mixed integer linear programming

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Water Truck Routing and Scheduling Optimization in Mining Operations with Inventory Function based on mixed integer linear programming 2017

Water Truck Routing and Scheduling Optimization in Mining Op...

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International Conference on Industrial Design Engineering (ICIDE)

作者： Solid, Kent Komarudin Univ Indonesia Fac Engn Depok Indonesia

ISBN: (纸本)9781450348669

Indonesia is one of the countries with the largest mining resources in the world, and this sector contributes a lot to the country's economy. However, the negative impacts resulting from this sector are also not to be taken lightly, especially for the environment. One of the pollution produced is dust contamination. If not addressed, it will cause various health and safety disorders in the mine. For that, the use of water trucks became common in mining to water the streets. It takes careful planning on the activity of water trucks in the mines to maximize their effectiveness. Therefore, this study aims to build a route design and water truck scheduling using mixed integer Linier programming that effectively reduce dust pollution. The result of this research is a route and schedule arrangement for water truck that can be used to guide the activity of water truck in mining and penalty calculation for each scenario.

关键词： Coal & mineral mining inventory function mixed integer linear programming water truck optimization dust pollution Capacitated Arc Routing Problem

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A High-Level Design Exploration of Heterogeneous Adders based on mixed integer linear programming

A High-Level Design Exploration of Heterogeneous Adders base...

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54th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Sosa, J. Montiel-Nelson, J. A. Garcia-Montesdeoca, J. C. Nooshabadi, Saeid Univ Las Palmas Gran Canaria Inst Appl Microelect Dept Elect Engn & Automat E-35017 Las Palmas Gran Canaria Spain Michigan Tech Dept Elect & Comp Engn Houghton MI USA

ISBN: (纸本)9781612848570

In this paper, we present a novel methodology based on mixed integer linear programming (MILP) for obtaining the complete design tradeoff curve of heterogeneous adders. For each optimal design point of the tradeoff curve, our approach determines both the number of subadders, the architecture of each subadder and the bit width of each subadder. In order to reduce the number of binary variables in the formulation of the MILP, we introduce a new modeling of non-convex curves. Comparisons using five different adder architectures implemented in a standard cells 65nm CMOS technology are shown. Experimental results reveal that the proposed design space exploration methodology is better, when compared with the best published work, up to 11.73 times and 2.16 times in average in terms of CPU time.

关键词： Adders CMOS logic circuits CMOS technology Delay Engines IP networks MILP programming Silicon adders binary variables design space exploration methodology heterogeneous adders high-level design exploration integer programming linear programming logic design mixed integer linear programming nonconvex curve modeling subadders tradeoff curve optimal design point

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Adaptive Multi-Agent System and mixed integer linear programming Optimization Comparison for Grid Stability and Commitment Mismatch in Smart Grids 11

Adaptive Multi-Agent System and Mixed Integer Linear Program...

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11th IEEE-PES Innovative Smart Grid Technologies Europe (IEEE-PES ISGT Europe)

作者： Zafar, S. Maurya, V Blavette, A. Camilleri, G. Ben Ahmed, H. Gleizes, M-P ENS Rennes SATIE Rennes France Univ Toulouse IRIT Toulouse France ENS Rennes SATIE CNRS Rennes France

ISBN: (纸本)9781665448758

Existing electrical networks are going through a transition and distributed energy resource, if not managed properly, can hinder this transition. Uncontrolled introduction of photovoltaics and electric vehicles in distribution networks would lead to substantial issues such as commitment mismatches, line congestions, voltage deviations, etc. This paper presents the use of a classical approach, mixed integer linear programming optimization, and a novel approach, adaptive multi-agent system, to solve the highlighted distribution side challenges by utilizing electric vehicles' storage capacity. This comparison serves as a great tool to benchmark the performance of the under-development adaptive multi-agent system methodology.

关键词： Multi-Agent Systems mixed integer linear programming Optimality Gap Electric Vehicles Balance Responsible Party Distribution Network Stability

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