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57th International Astronautical Congress

作者： Gil-Fernandez, Jesus Tarabini, Lorenzo Graziano, Mariella Gomez-Tierno, M. A. GMV SA Madrid 28760 Spain

A new hybrid direct-indirect optimization algorithm is presented to compute the minimum-time transfer between two orbits, including the phasing with a desired spacecraft. Very-low thrust means several hundred revolutions to perform the large change in orbital elements. The optimal control solution of the fast-evolution problem combined with a direct method for the secular trajectory avoids the numerical instability arising in very long propagations, decreases the computational time, reduces the sensitivity to the initial guess and provides a feasible transfer at every optimization step. Optimization of transfers from GTO to GEO is presented and two types of trajectories are analysed, sub-synchronous (apogee constrained below GEO altitude) and super-synchronous (free apogee altitude). The optimization of a transfer from LEO to a very high orbit (11 ' 23 R E) is presented, showing the applicability of the method to different problems. A guidance algorithm is presented to compensate the deviations of the real trajectory from the optimal one due to off-nominal conditions. The results in closed-loop simulation of the guidance scheme to compensate detenninistic perturbations not considered in the optimization show good performances in both analysed missions.

关键词： trajectory optimization low-thrust optimal control non-linear programming guidance

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Improved PSO for optimizing the performance of intrusion detection systems

Improved PSO for optimizing the performance of intrusion det...

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5th International Symposium on Intelligent Systems Technologies and Applications (ISTA) / International Conference on Applied Soft Computing and Communication Networks (ACN)

作者： Dickson, Anne Thomas, Ciza Coll Engn Trivandrum Kerala India

Intrusion detection system is a second layer of defence in a secured network environment. When comes to an IoT platform, the role of IDS is very critical since it is highly vulnerable to security threats. For a trustworthy intrusion detection system in a network, it is necessary to improve the true positives with minimum false positives. Research reveals that the true positive and false positive are conflicting objectives that are to be simultaneously optimized and hence their trade-off always exists as a major challenge. This paper presents a method to solve the tradeoff among these conflicting objectives using multi-objective particle swarm optimization approach. We conducted empirical analysis of the system with multiple machine learning classifiers. Experimental results reveals that this technique with J48 classifier gives the highest gbest value 10.77 with minimum optimum value of false positive 0.02 and maximum true positive 0.995. Empirical evaluation shows an incredible improvement in Pareto set in the objective function space by attaining an optimum point.

关键词： Intrusion detection system receiver operating characteristics particle swarm optimization pareto front multi-objective optimization non-linear programming

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Total solar irradiance fluctuation effects on sailcraft-Mars rendezvous

Total solar irradiance fluctuation effects on sailcraft-Mars...

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6th IAA Symposium on Missions to the Outer Solar System and Beyond

作者： Vulpetti, Giovanni GalileianPlus SrI Rome Italy Telespazio SpA Rome Italy

This paper is the second one of a research line whereupon the variations of the total solar irradiance are explicitly included in a large high-precision computer code for sailcraft trajectory optimization. Sailcraft-Mars rendezvous has been chosen for studying such effects. It turns out that irradiance-fluctuation perturbations are large in this trajectory type. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Total solar irradiance Solar sailing Lightness vector non-linear programming

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A quantified assessment of the relationship between the reliability and entropy of water distribution systems

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ENGINEERING OPTIMIZATION 2000年第2期33卷 179-199页

作者： Tanyimboh, TT Templeman, AB Univ Liverpool Dept Civil Engn Liverpool L69 3GQ Merseyside England

Several researchers have suggested that it might be possible to use entropy as a general performance indicator for water distribution systems. It has several advantages over other performance and reliability indices, for example, it is extremely rapid and far easier to calculate than other measures, has minimal data requirements and lends itself to direct incorporation into design optimization frameworks. This paper summarises the first proper attempt to investigate the apparent relationship between the entropy and reliability of water distribution systems. A maximum entropy-constrained approach was used to generate designs for a sample water distribution system which. along with traditional minimum-cost designs, formed the basis of this study. By varying the layout, number of loops and links and reversing the direction of flow in some pipes, it is shown statistically that the correlation between entropy and reliability is strong. Based on the results, a new method for sizing the pipes of water distribution systems is proposed. It is quick, easy to implement, finds optimal pipe sizes, does not require non-linear programming and always guarantees a high level of reliability.

关键词： entropy reliability design optimization water distribution systems redundancy linear programming non-linear programming statistical correlation

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Real-Coded Genetic Algorithm for Solving Generalized Polynomial programming Problems

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JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS 2007年第4期11卷 358-364页

作者： Wu, Jui-Yu Chung, Yun-Kung Yuan Univ Dept Ind Engn & Management 135 Yuan Tung Rd Chungli 320 Taiwan

Generalized polynomial programming (GPP) is a non-linear programming (NLP) method based on a non-convex objective function, which is subject to nonconvex inequality constraints. Hence, a GPP problem has multiple local optima in its constrained solution space. General NLP techniques use local optimization, and therefore do not easily solve GPP problems. Some deterministic global optimization approaches have been developed to overcome this drawback of NLP methods. Although these approaches yield a global solution to a GPP problem, they can be mathematically tedious. Therefore, this study presents a real-coded genetic algorithm (RGA), which is a stochastic global optimization method, to find a global solution to a GPP problem. The proposed RGA is used to solve a set of GPP problems. The best solution obtained by the RGA is compared with the known global solution to each test problem. Numerical results show that the proposed RGA converges to a global solution to a GPP problem.

关键词： generalized polynomial programming non-linear programming genetic algorithm

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Intelligent system application in environment and waste management: A review

Intelligent system application in environment and waste mana...

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2023 International Conference on Advances in Materials, Mechanics, Mechatronics and Manufacturing, IC4M 2023

作者： Bai, V. Ramani Kangadharan, G. Deprizon, S. Taha, M.J. Dhanush, G. Gopinath, R. Faculty of Engineering Technology & Built Environment UCSI University Kuala Lumpur Malaysia Kuala Lumpur Malaysia University of Cambridge United Kingdom Sdn. Bhd. Selayang Malaysia

Waste management issues involve uncertainties represented as intervals, random variables, and fuzzy sets related to intelligent processing. Over the last two decades, intelligent programming approaches have been increasingly developed and applied to address waste management challenges in uncertain scenarios. This paper provides an overview of recent advancements, applications, obstacles, and limitations associated with intelligent programming techniques in the context of supporting environment and waste management. The findings reveal that a majority of intelligent programming methods fall into categories high-level optimization methods, fuzzy programming, artificial neural networks, neuro-fuzzy robust, and hybrid programming. Areas demanding further research include sensitivity analysis of intelligent processing, combining intelligent programming with other modelling approaches, such as life cycle assessment, multiple-criteria decision analyses, and waste flow simulation, to promote sustainable waste management. Developing more efficient algorithms for solving the proposed methods, and establishing connections between waste management and its environmental consequences, including climate change, air pollution, greenhouse gas emissions, and leachate pollution, within an intelligent optimization framework are further areas of research in the future. Copyright © 2024 Elsevier Ltd. All rights reserved.

关键词： Advanced technology Environmental issues Fuzzy logic methods Intelligent programming non-linear programming Sustainable system

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A Computing Based Design Model of Pneumatic Driven Variable Buoayncy System for Autonomous Underwater Vehicles

A Computing Based Design Model of Pneumatic Driven Variable ...

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MTS/IEEE Oceans Conference

作者： Sahoo, Patitapaban Sharma, R. Asokan, T. IIT Madras Dept Ocean Engn Design & Simulat Lab Madras 36 TN India IIT Madras Dept Ocean Engn Madras 36 TN India

ISBN: (纸本)9781509015375

In the era of modern computing based environment, the process of design is conceptualized, implemented and tested in a close loop integrating different modules of design, manufacturing and usages. In this regard, this paper presents a computing based design model for the design of a 'Pneumatic Driven Variable Buoyancy System (PDVBS)' for 'Autonomous Underwater Vehicles (AUVs)'. The presented design model is modular in architecture and integrates the design of PDVBS with design of AUV. The design approach is derived from the basic and advanced principles of mechanics and the approach is defined in the 'Computer Aided Design (CAD)' model in terms of different modules with implementation in Matlab*(TM). Finally, we present a design example of a PDVBS for depth rating up to 4200 m with application focused on a large AUV of length 7 m to show the efficiency and applicability of our proposed design model.

关键词： Variable buoyancy system Pneumatic driven system Underwater vehicle Computing model System dynamics non-linear programming

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Low-energy localized clustering: An adaptive cluster radius configuration scheme for topology control in wireless sensor networks

Low-energy localized clustering: An adaptive cluster radius ...

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61st IEEE Vehicular Technology Conference

作者： Kim, J Kim, S Kim, D Lee, W Kim, E Korea Univ Dept Comp Sci & Engn Seoul 136701 South Korea

ISBN: (纸本)0780388879

This paper addresses an adaptive and dynamic localized scheme unique to hierarchical clustering protocols in wireless sensor networks, while reducing the consumption of residual energy of cluster heads and as a result delivering a prolonged the sensor network lifetime. Our proposed scheme, Low-Energy Localized Clustering (LLC), aims to minimize energy consumption of cluster heads while the entire sensor network is still being covered. For achieving this goal, LLC dynamically regulates the radius of each cluster. Through a simulation based performance of this algorithm, LLC, we show that our novel cluster radius configuration algorithm achieves the desirable properties.

关键词： wireless sensor network localized clustering topology control non-linear programming

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Comparative Implementation of Numerical Integration Methods for Transient Stability Constrained Optimal Power Flow

Comparative Implementation of Numerical Integration Methods ...

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IEEE International Conference on Environment and Electrical Engineering (EEEIC) / IEEE Industrial and Commercial Power Systems Europe (ICPS Europe)

作者： Arredondo, Francisco Daniel Castronuovo, Edgardo Ledesma, Pablo Leonowicz, Zbigniew Univ Carlos III Madrid Dept Elect Engn Leganes Spain Wroclaw Univ Sci & Technol Fac Elect Engn Wroclaw Poland

ISBN: (纸本)9781538651865

Transient Stability Constrained Optimal Power Flow (TSCOPF) is a non-linear mathematical programming problem that optimizes the operation of power systems considering steady state and dynamic constrains. TSCOPF models extend the OPF solution by considering the dynamic behavior of the system. One of the main approaches in TSCOPF studies discretizes the differential equations representing the dynamics of the system and includes them in the optimization problem. This paper evaluates the impact of numerical integration methods and time steps on TSCOPF. The results show that: 1) the forward Euler method obtains the most conservative representation for all cases evaluated;2) as the integration time step increases, the backward Euler method and the trapezoidal rule tend to dampen electromechanical oscillations;and 3) the adequate use of a variable integration time step achieves a reduction in the number of equations, variables and computation times, while maintaining the accuracy on the results.

关键词： Power system transient stability numerical integration methods non-linear programming optimal power flow

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Alternating heuristic and exact method for the leader-follower facility location and design problem 12

Alternating heuristic and exact method for the leader-follow...

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12th International Conference on Electronics Computer and Computation (ICECCO)

作者： Kochetov, Yury Sokolova, Irina Amirgaliyeva, Saltanat Amirgaliyeva, Zhazira Inst Informat & Computat Technol Pushkin St 125 Alma Ata 050010 Kazakhstan Novosibirsk State Univ Novosibirsk 630090 Russia Suleyman Demirel Univ Kaskelen 040900 Kazakhstan Kazakh Natl Univ Alma Ata 050040 Kazakhstan

ISBN: (纸本)9781509001996

We study the following discrete facility location game. Two players, a leader and a follower, open facilities and compete to attract clients from a given market. Each player has a budget and maximizes own market share. Each client splits own demand probabilistically over all opened facilities by the gravity rule. The goal is to find the location and design of the leader facilities to maximize his market share. We present an alternating heuristic and exact method for this game. We rewrite the problem as mixed integer linear program with exponential number of constraints. In our method, we start with small subset of constraints and iteratively enlarge it until upper and lower bounds not coincide. Computational results are discussed.

关键词： competitive facility location Stackelberg game bi-level optimization metaheuristic non-linear programming

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