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5th International Conference on Informatics in Control, Automation and Robotics

作者： Cruz, Filipe Coelho, Antonio Reis, Luis Paulo Univ Porto Fac Engn P-4200465 Roberto Frias Portugal

ISBN: (纸本)9789898111302

Expeditious modelling of virtual urban environments consists of generating realistic 3d models from limited information. It has several practical applications but typically suffers from a lack of accuracy in the parameter values that feed the modeller. By gathering small amounts of information about certain key urban areas, it becomes possible to feed a system that automatically compares and adjusts the input parameter values to find optimal solutions of parameter combinations that resemble the real life model. These correctly parameterized rules can then be reapplied to generate virtual models of real areas with similar characteristics to the referenced area. Based on several nature inspired metaheuristic algorithms such as genetic algorithms, simulated annealing and harmony search, this paper presents a new hybrid metaheuristic algorithm capable of optimizing functions with both discrete and continuous parameters and offer competitive results in a highly neglected field of application.

关键词： metaheuristics optimization algorithms optimization systems expeditious modelling

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Modeling Capacity of Road Network Based on Level of Service of Network

Modeling Capacity of Road Network Based on Level of Service ...

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International Conference on Intelligent Computation Technology and Automation

作者： Li Binglin Li Feng Wang Renying Changsha Univ Sci & Technol Sch Transportat Engn Changsha 410076 Peoples R China Tongji Univ Sch Transport Engn Shanghai 201804 Peoples R China

ISBN: (纸本)9780769533575

Urban road traffic is the foundation of the existence and development of urban society, therefore the calculation of the capacity of road network is an urgent problem. Based on the bi-level programming model of the road network capacity, the concept of the level of network service is introduced. Considering the impact of network service level on the whole network, this paper has constructed a network capacity calculation model based on level of service of network, and solved it using a kind of hybrid optimization algorithm combined genetic algorithm and simulate annealing (GASA). Ultimately, a simple network has been provided to prove the model as well as the algorithm.

关键词： road network Network Legal Services network capacity optimization algorithms Genetic Algorithm (GA) simple network Urban road Computational modeling

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New Coupled EM and Circuit Simulation Flow for Integrated Spiral Inductor by Introducing Symbolic Simplified Expressions

New Coupled EM and Circuit Simulation Flow for Integrated Sp...

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IEEE International Symposium on Industrial Electronics

作者： Ciccazzo, Angelo Halfmann, Thomas Marotta, Angelo Nicosia, Giuseppe Rinaudo, Salvatore Stracquadanio, Giovanni Venturi, Alberto ST Microelect Stradale Primosole 50 I-95121 Catania Italy Univ Catania Dept Math & Comp Sci I-95125 Catania Italy Fraunhofer Inst Tech & Wirtschaftsmat D-67663 Kaiserslautern Germany

ISBN: (纸本)9781424416653

Micro-electronics component and circuit design requires long computation time;to reduce this time, the use of simplification techniques has been introduced. In order to obtain a first validation of the method, a first test case is presented;the simplification techniques have been applied to the analytical expression of Y parameters of an inductor equivalent circuit. The resulting expressions have been used in the fitting process in order to reproduce the behaviour of a simulated inductor. Five different optimization algorithms, both deterministic (POWELL and DIRECT) and stochastic (CRS, CRS ENHANCED and OPTIA) have been tested for the fitting. The result of the introduction of the simplification techniques has been the reduction of the running time during the fitting. From an optimization point of view, the best results have been obtained by the stochastic algorithms CRS, and OPTIA.

关键词： AND GATE y-parameters simplification spiral inductor computational time fitting process inductors optimization algorithms Runtime CASING INSPECTION

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SIMULATION-BASED optimization FOR THE QUAY CRANE SCHEDULING PROBLEM 08

SIMULATION-BASED OPTIMIZATION FOR THE QUAY CRANE SCHEDULING ...

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Winter Simulation Conference (WSC 2008)

作者： Pasquale Legato Rina Mary Mazza Roberto Trunfio University of Calabria Rende (CS) Italy CESIC NEC Italy Rende (CS) Italy

ISBN: (纸本)9781424427086

Maritime terminals of pure transhipment are emerging logistic realities in long-distance containerized trade. Here, complex activities of resource allocation and scheduling should be optimized in a dynamic, non deterministic environment. The assignment of expensive quay cranes to multiple vessel-holds for container discharging and loading operations is a major problem, whose solution affects the operational performance of the whole terminal container. In OR literature, this problem is known as the quay crane scheduling problem. With the objective of minimizing the vessel's overall completion time, we first give our IP formulation and then, under the more realistic assumption that discharge-loading times are non deterministic, we focus on a simulation-based optimization approach which embodies the IP formulation. Two different simulation optimization algorithms are tailored to the problem: simulated annealing and adaptive balanced explorative and exploitative search. Preliminary numerical results are presented on real vessel data.

关键词： QUAY CRANE loading operations optimization algorithms operating performance Completion time Resource utilization EIS IMPLEMENTATION PLANS CONTAINERS

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Solving multi-objective optimization problems by RasID-GA

Solving multi-objective optimization problems by RasID-GA

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SICE Annual Conference

作者： Marina Ogata Dongkyu Sohn Shingo Mabu Kaoru Shimada Kotaro Hirasawa Graduate School of Information Production and Systems Waseda University Kitakyushu-shi Fukuoka Japan

ISBN: (纸本)9784907764302

This paper aims to solve multi-objective problems by adaptive random search with intensification and diversification combined with genetic algorithm (RasID-GA). Problems with multi-objectives are common in engineering, economics, computer science, and many others field of studies. It has been a challenge for the researchers to develop algorithms able to solve this kind of problem. RasID is an optimization algorithm, which is good at finding local optima, but its diversified search isnpsilat so efficient, for this reason, we combined RasID with genetic algorithms (GA), which is superior at finding global optima. In this paper, RasID-GA is used to find the Pareto- optimal solutions. RasID-GA is compared with the algorithm of NSGA-II using well known benchmarks.

关键词： Multi-Objective RasID-GA Pareto-Optimal Solutions Multi-Objective Evolutionary Algorithm (MOEA) Genetic Algorithm (GA) optimization algorithms Solve algorithms diversification FINDINGS Intensification computer science Heterogeneous BENCHMARKS

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A Novel Self-Adaptive Casting Net-based Particle Swarm optimization

A Novel Self-Adaptive Casting Net-based Particle Swarm Optim...

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第七届网格与协同计算国际会议(Seventh International Conference on Grid and Cooperative Computing GCC 2008)

作者： Hongbo Tian Xiaoshe Dong Yiduo Mei Taiqiang Lv Xiaoyi Zhao Department of Computer Science and Technology Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9781424432806;9780769534497

Prematurity is a troublesome problem that has to be faced and got rid of by many optimization algorithms, especially the Particle Swarm optimization (PSO). To combat with prematurity, this paper proposes a selfadaptive casting net mechanism that is able to search global fitness efficiently. To keep diversity of particles, the self-adaptive casting net mechanism tunes parameters dynamically according to the number of iteration. Based on the proposed casting net mechanism, a novel Self-adaptive Casting Net-based Particle Swarm optimization (SCNPSO) is presented. Experiments were carried out to compare the standard PSO with SCNPSO with various parameters for selfadaptive and different strategies for moving based on benchmark functions of optimization. Experimental results show that SCNPSO outperforms PSO due to adjusting parameters self-adaptively and strategies for moving.

关键词： Particle swarm optimization self-adaptive Casting Premature Infant Moving adjustable parameter parametric subharmonic oscillator optimization algorithms Premature Obstetric Labor

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COMPUTATIONAL GEOMETRIC OPTIMAL CONTROL OF RIGID BODIES

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COMMUNICATIONS IN INFORMATION AND SYSTEMS 2008年第4期8卷 445-472页

作者： Lee, Taeyoung Leok, Melvin McClamroch, N. Harris Florida Inst Technol Dept Mech & Aerosp Engn Melbourne FL 32901 USA Purdue Univ Dept Math W Lafayette IN 47907 USA Univ Michigan Dept Aerosp Engn Ann Arbor MI 48109 USA

This paper formulates optimal control problems for rigid bodies in a geometric manner and it presents computational procedures based on this geometric formulation for numerically solving these optimal control problems. The dynamics of each rigid body is viewed as evolving on a configuration manifold that is a Lie group. Discrete-time dynamics of each rigid body are developed that evolve on the configuration manifold according to a discrete version of Hamilton's principle so that the computations preserve geometric features of the dynamics and guarantee evolution on the configuration manifold;these discrete-time dynamics are referred to as Lie group variational integrators. Rigid body optimal control problems are formulated as discrete-time optimization problems for discrete Lagrangian/Hamiltonian dynamics, to which standard numerical optimization algorithms can be applied. This general approach is illustrated by presenting results for several different optimal control problems for a single rigid body and for multiple interacting rigid bodies. The computational advantages of the approach, that arise from correctly modeling the geometry, are discussed.

关键词： Body dynamics Manifolds Optimal control Lie group Rigid Rigid bodies discrete-time optimization algorithms

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Comparative Analysis of Genetic Algorithm and Ant Colony Algorithm on Solving Traveling Salesman Problem

Comparative Analysis of Genetic Algorithm and Ant Colony Alg...

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IEEE International Workshop on Semantic Computing and Systems, WSCS

作者： Kangshun Li Lanlan Kang Wensheng Zhang Bing Li School of Information Engineering Jiangxi University of Science and Technology China Institute of Automation Chinese Academy and Sciences China State Key Laboratory of Engineering Software Wuhan University of China China

ISBN: (纸本)9780769533162

Ant Colony Algorithm and Genetic Algorithm (GA), two bionic-inspired optimization algorithms, have great potentials to solve the combination optimization problems, respectively used in solving traveling salesman problem, but there are some shortcomings if only one of them is used to solve TSP. Performance comparative analysis have been done by using ACA and GA respectively in solving TSP in this paper. The experiments show the advantages and disadvantages used only ACA or GA, we can overcome the shortcomings if GA and ACA are combined to solve TSP and get faster convergent speed and more accurate results compared with only using ACA or GA.

关键词： travelling salesman problems ant algorithm Gallium Genetic Algorithm (GA) optimization algorithms Solve

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Population-Variance and Explorative Power of Harmony Search: An Analysis

Population-Variance and Explorative Power of Harmony Search:...

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International Conference on Digital Information Management (ICDIM)

作者： Arpan Mukhopadhyay Anwit Roy Sourav Das Swagatam Das Ajith Abraham Department of Electronics and Telecommunication Engineering Jadavpur University Kolkata India Center of Excellence for Quantifiable Quality of Service Norwegian University of Science and Technology Norway

ISBN: (纸本)9781424429165

This paper presents a simple mathematical analysis of some features of the Harmony Search algorithm (HS). HS is a recently developed derivative-free optimization algorithm, which draws inspiration from the musical process of searching for a perfect state of harmony. This work analyses the evolution of the population-variance over successive generations in HS and thereby draws some important conclusions regarding the explorative power of HS. Experimental results have been provided to validate the theoretical treatment. A simple modification of the classical HS has been proposed in the light of the mathematical analysis undertaken here.

关键词： Hydrogen Sulfide (H2S3) mathematical analysis Perfect state Respiratory Inspiration inspiration optimization algorithms Energy sources Power (Psychology)

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Parallel Evaluation of Composite Aggregate Queries

Parallel Evaluation of Composite Aggregate Queries

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IEEE 24th International Conference on Data Engineering (ICDE 2008), vol.1

作者： Lei Chen Christopher Olston Raghu Ramakrishnan Computer Sciences Department University of Wisconsin Madison Madison WI USA Yahoo Research Santa Clara CA USA

ISBN: (纸本)9781424418367;1424418364

Aggregate measures summarizing subsets of data are valuable in exploratory analysis and decision support, especially when dependent aggregations can be easily specified and computed. A novel class of queries, called composite subset measures, was previously introduced to allow correlated aggregate queries to be easily expressed. This paper considers how to evaluate composite subset measure queries using a large distributed system. We describe a cross-node data redistribution strategy that takes into account the nested structure of a given query. The main idea is to group data into blocks in "cube space", such that aggregations can be generated locally within each block, leveraging previously proposed optimizations per-block. The partitioning scheme allows overlap among blocks so that sliding window aggregation can be handled. Furthermore, it also guarantees that the final answer is the union of local results with no duplication and there is no need for the expensive data combination step. We identify the most important partitioning parameters and propose an optimization algorithm. We also demonstrate effectiveness of the optimizer to minimize the query response time.

关键词： Reaction Time Nested Structure optimization algorithms Distributed Systems aggregates Blocks

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