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performance of an Autonomous Multi-Maneuver algorithm for Lunar Trans-Earth Injection

JOURNAL OF SPACECRAFT AND ROCKETS 2012年第1期49卷 165-174页

作者： Whitley, Ryan J. Ocampo, Cesar A. Williams, Jacob NASA Johnson Space Ctr Houston TX 77068 USA Univ Texas Austin Dept Aerosp Engn & Engn Mech Austin TX 78712 USA ERC Inc ESCG Houston TX 77058 USA

Using a fully analytic initial estimate, a self-starting algorithm that constructs a flyable multiburn maneuver sequence to transfer a spacecraft from a closed low-lunar parking orbit to a desired Earth-entry state is developed and implemented. The algorithm is built to support the need for a human spacecraft to abort anytime during the mission and return automatically from a variety of lunar mission scenarios. This study presents a large set of representative test cases for algorithm evaluation, including highly constrained Earth-entry interface states that return the spacecraft to a specific landing site. For all cases, an optimal finite-burn solution is obtained successfully in computation time suitable for real-time on-board operation.

关键词： Trans Earth Injection Earth Propellant Elliptical Orbit Flight Path Angle Sequential Quadratic Programming Lift to Drag Ratio Thrust to Weight Ratio algorithm performance Search algorithm

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A comprehensive investigation into the performance of genetic algorithm for effective shipyard topological layout

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART M-JOURNAL OF ENGINEERING FOR THE MARITIME ENVIRONMENT 2022年第3期236卷 726-740页

作者： Turk, Abdullah Gurgen, Samet Ozkok, Murat Altin, Ismail Karadeniz Tech Univ Dept Naval Architecture & Marine Engn Trabzon Turkey Iskenderun Tech Univ Dept Naval Architecture & Marine Engn Antakya Turkey

Shipyards have large departments or facilities. It is essential to make an effective topological layout plan since the initial investment cost of these departments is high. Topological layout is an optimization problem and Genetic algorithm (GA) is generally used in the literature. The selection of effective genetic algorithm approaches and operators are very important to improve the performance of the optimization. This study investigates an effective solution to the shipyard topological layout using a Quadratic Assignment Problem (QAP) model with classic and elitist GA approaches. Besides, genetic operators that have significant effects on exploitation and exploration capabilities are analyzed. Therefore, 126 experiments were run with 13 different operators. The results obtained from the classic and elitist GA approach were evaluated individually and compared with each other. It was observed that the elitist GA approach has a superior performance compared to the classic GA approach. This study is the most comprehensive and practical study on the performance of the GA for topological layout of the shipyard in the literature.

关键词： Shipyard topological layout elitist genetic algorithm classic genetic algorithm optimization algorithm performance

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performance Analysis of a Dual Quaternion Guidance algorithm applicable during Lunar Approach with a Hazard Avoidance Maneuver

Performance Analysis of a Dual Quaternion Guidance Algorithm...

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AIAA SciTech Forum

作者： Doll, Javier A. Wagner, Samuel T. Fritz, Matthew P. Jang, Jiann-Woei Harper, Jeanette M. Smith, Kyle W. Acikmese, Behcet Pedrotty, Samuel M. Mendeck, Gavin F. Charles Stark Draper Lab Cambridge MA USA NASA Johnson Space Ctr Washington DC 20546 USA Odyssey Space Res Houston TX USA Univ Washington Seattle WA 98195 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

There is currently a need for advanced guidance and targeting algorithms that can provide real-time trajectories in the presence of state and vehicle constraints during powered descent. The Safe & Precise Landing Integrated Capabilities Evolution (SPLICE) program aims to mature Hazard Detection (HD) technology along with advanced navigation and guidance algorithms. This paper will report the overall performance of the SPLICE Dual Quaternion Guidance (DQG) algorithm which is a 6-Degree-of-Freedom (6-DOF) convex optimization-based guidance algorithm that can enforce multiple vehicle and state constraints required for Hazard Detection Lidar (HDL) scans during the approach phase. DQG was tested in a closed-loop lunar descent simulation with realistic HDL sensing constraints in a Monte Carlo assessment of 1000 dispersed runs.

关键词： Navigation algorithm Dual Quaternions Three Degrees of Freedom Linear Time Invariant Convex Optimization LIDAR algorithm performance Guidance, Navigation, and Control Propellant Slosh Attitude Control System

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EXAMINING THE RELATIONSHIP BETWEEN algorithm STOPPING CRITERIA AND performance USING ELITIST GENETIC algorithm

EXAMINING THE RELATIONSHIP BETWEEN ALGORITHM STOPPING CRITER...

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2010 Winter Simulation Conference

作者： Kim, Jin-Lee Calif State Univ Long Beach Long Beach CA 90840 USA

ISBN: (纸本)9781424498642

A major disadvantage of using a genetic algorithm for solving a complex problem is that it requires a relatively large amount of computational time to search for the solution space before the solution is finally attained. Thus, it is necessary to identify the tradeoff between the algorithm stopping criteria and the algorithm performance. As an effort of determining the tradeoff, this paper examines the relationship between the algorithm performance and algorithm stopping criteria. Two algorithm stopping criteria, such as the different numbers of unique schedules and the number of generations, are used, while existing studies employ the number of generations as a sole stopping condition. Elitist genetic algorithm is used to solve 30 projects having 30-Activity with four renewable resources for statistical analysis. The relationships are presented by comparing means for algorithm performance measures, which include the fitness values, total algorithm runtime in millisecond, and the flatline starting generation number.

关键词： algorithm performance algorithm stopping criteria elitist genetic algorithm genetic algorithms

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Attitude-determination filtering via extended quaternion estimation

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2000年第2期23卷 206-214页

作者： Psiaki, ML Cornell Univ Ithaca NY 14853 USA

The quaternion estimation (QUEST) batch attitude-determination algorithm has been extended to work in a general Kalman-filter framework. This has been done to allow the inclusion of a complicated dynamics model and to allow the estimation of additional quantities beyond the attitude quaternion. The QUEST algorithm, which works with vector attitude observations, serves as a starting point because it is able to work with a poor (or no) first guess of the attitude. This paper's extended version of QUEST uses square-root information filtering techniques and linearization of the dynamics to propagate the state and its covariance. The measurement update problem is solved by a technique that is an extension of the original QUEST algorithm's eigenvalue/eigenvector solution. The paper demonstrates the new algorithm's performance on an attitude determination problem that uses star-tracker and rate-gyro measurements. The new algorithm is able to converge from initial attitude errors of 180 deg and initial rate-gyro bias errors as large as 2400 deg/h.

关键词： Quaternions Attitude Dynamics algorithm performance Attitude Determination algorithms Quadratic Programming White Noise Numerical Integration Euler Equations Probability Density Functions Spacecraft Missions

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Quality versus accuracy: result of a reanalysis of protein-binding microarrays from the DREAM5 challenge by using BayesPI2 including dinucleotide interdependence

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BMC BIOINFORMATICS 2014年第1期15卷 1-15页

作者： Wang, Junbai Norwegian Radium Hosp Oslo Univ Hosp Dept Pathol N-0310 Oslo Norway

Background: Computational modeling transcription factor (TF) sequence specificity is an important research topic in regulatory genomics. A systematic comparison of 26 algorithms to learn TF-DNA binding specificity in in vitro protein-binding microarray (PBM) data was published recently, but the quality of those examined PBMs was not evaluated completely. Results: Here, new quality-control parameters such as principal component analysis (PCA) ellipse is proposed to assess the data quality for either single or paired PBMs. Additionally, a biophysical model of TF-DNA interactions including adjacent dinucleotide interdependence was implemented in a new program - BayesPI2, where sparse Bayesian learning and relevance vector machine are used to predict unknown model parameters. Then, 66 mouse TFs from the DREAM5 challenge were classified into two groups (i.e. good vs. bad) based on the paired PBM quality-control parameters. Subsequently, computational methods to model TF sequence specificity were evaluated between the two groups. Conclusion: Results indicate that both the algorithm performance and the predicted TF-binding energy-level of a motif are significantly influenced by PBM data quality, where poor PBM data quality is linked to specific protein domains (e.g. C2H2 DNA-binding domain). Especially, the new dinucleotide energy-dependent model (BayesPI2) offers great improvement in testing prediction accuracy over the simple energy-independent model, for at least 21% of analyzed the TFs.

关键词： algorithm performance Relevance Vector Machine Position Weight Matrice Sparse Bayesian Learning DREAM5 Challenge

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tttplots compare a perl program to compare time-to-target plots or general runtime distributions of randomized algorithms

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OPTIMIZATION LETTERS 2015年第3期9卷 601-614页

作者： Ribeiro, Celso C. Rosseti, Isabel Univ Fed Fluminense Dept Comp Sci BR-24210240 Niteroi RJ Brazil

Run time distributions or time-to-target plots display on the ordinate axis the probability that an algorithm will find a solution at least as good as a given target value within a given running time, shown on the abscissa axis. Given a pair of different randomized algorithms and , we describe a numerical method that gives the probability that finds a solution at least as good as a given target value in a smaller computation time than , for the case where the runtimes of each of the two algorithms follow any runtime distribution. An illustrative example of a numerical application is also reported. We describe the perl program tttplots-compare, developed to compare time-to-target plots or general runtime distribution for measured CPU times of any two randomized heuristics. A listing of the perl program is given, and the program can also be downloaded from http://***/similar to celso/compare-tttplots..

关键词： Randomized algorithms GRASP tttplots Metaheuristics Stochastic local search Runtime distributions algorithm performance Comparison of two algorithms

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Search bias in ant colony optimization: On the role of competition-balanced systems

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IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 2005年第2期9卷 159-174页

作者： Blum, C Dorigo, M Univ Politecn Cataluna Dept Llenguatages & Sustemes Informat E-08034 Barcelona Spain Free Univ Brussels IRIDIA B-01050 Brussels Belgium

One of the problems encountered when applying ant colony optimization (ACO) to combinatorial optimization problems is that the search process is sometimes biased by algorithm features such as the pheromone model and the solution construction process. Sometimes this bias is harmful and results in a decrease in algorithm performance over time, which is called second-order deception. In this work, we study the reasons for the occurrence of second-order deception. In this context, we introduce the concept of competition-balanced system (CBS), which is a property of the combination of an ACO algorithm with a problem instance. We show by means of an example that combinations of ACO algorithms with problem instances that are not CBSs may suffer from a bias that leads to second-order deception. Finally, we show that the choice of an appropriate pheromone model is crucial for the success of the ACO algorithm, and it can help avoid second-order deception.

关键词： algorithm performance ant colony optimization (ACO) metaheuristics search bias

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BIRTH OF A SALESMAN

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 1988年第5期11卷 415-420页

作者： SHAW, JJ JAMES, RM GRUNBERG, DB ALPHATECH INC MKT RES & DEVBURLINGTONMA 01803

The AIAA Artificial Intelligence Design Challenge is eccentric and intriguing, combining features from traveling salesman and stochastic optimization problems together with several side constraints thrown in for additional appeal. The challenge is to devise a solution algorithm that will reliably find optimal (or near optimal) solutions and can be extended to more general problems. We present our algorithm for this challenge in this paper. The fundamental algorithm for finding near-optimal solutions is disarmingly simple and can be made quite efficient through the introduction of several bounds on the problem. The reader will quickly discover that these bounds do not require a deep understanding of traveling salesman algorithms and should enjoy devising additional bounds to add to the potpourri. © 1988 American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： algorithm performance Artificial Intelligence Stochastic Optimization Optimization algorithm Greedy algorithm Gas Dynamics Kinetic Theory of Gases Aerodynamics Planetary Atmospheres Search algorithm

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Lower Bounds on performance of Metric Tree Indexing Schemes for Exact Similarity Search in High Dimensions

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algorithmICA 2013年第2期66卷 310-328页

作者： Pestov, Vladimir Univ Ottawa Dept Math & Stat Ottawa ON K1N 6N5 Canada

Within a mathematically rigorous model, we analyse the curse of dimensionality for deterministic exact similarity search in the context of popular indexing schemes: metric trees. The datasets X are sampled randomly from a domain Omega, equipped with a distance, rho, and an underlying probability distribution, mu. While performing an asymptotic analysis, we send the intrinsic dimension d of Omega to infinity, and assume that the size of a dataset, n, grows superpolynomially yet subexponentially in d. Exact similarity search refers to finding the nearest neighbour in the dataset X to a query point omega a Omega, where the query points are subject to the same probability distribution mu as datapoints. Let denote a class of all 1-Lipschitz functions on Omega that can be used as decision functions in constructing a hierarchical metric tree indexing scheme. Suppose the VC dimension of the class of all sets {omega:f(omega)a parts per thousand yena}, aaa"e is o(n (1/4)/log(2) n). (In view of a 1995 result of Goldberg and Jerrum, even a stronger complexity assumption d (O(1)) is reasonable.) We deduce the Omega(n (1/4)) lower bound on the expected average case performance of hierarchical metric-tree based indexing schemes for exact similarity search in (Omega,X). In paricular, this bound is superpolynomial in d.

关键词： algorithms and data structures Indexing schemes Similarity search Vapnik-Chernonenkis theory algorithm performance

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