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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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SIMULATION-BASED, OPTIMIZED SCHEDULING OF LIMITED BAR-BENDERS OVER MULTIPLE BUILDING SITES 08

SIMULATION-BASED, OPTIMIZED SCHEDULING OF LIMITED BAR-BENDER...

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Winter Simulation Conference (WSC 2008)

作者： Hoi-Ching Lam Ming Lu Hong Kong Polytechnic University Hong Kong China

ISBN: (纸本)9781424427086

In the construction industry, a specialist subcontractor manages a taskforce of single-skilled laborers to work on multiple construction sites, aiming to minimize the total cost and stay profitable and competitive. This paper presents a simulation-based approach to assist the subcontractor in scheduling the application of limited laborer resources to handle jobs over multiple concurring sites. Factoring in technological constraints, repetitive building cycles, alternative method options, and the limited quantity of skilled laborers, we resort to computer power (including simulation and optimization algorithms resulting from recent research) in search of the best combination of construction methods at individual sites along with the optimum size of labor force, aimed to find the least cost for completing the jobs at all sites. A case study of bar-bender scheduling over three sites by use of an in-house computer tool results in the optimum method combinations, the optimum crew size, and the optimum resource schedule.

关键词： Construction methods Buildings Labor Force Laborers optimization algorithms Construction Industry Total Costs Optimum multiple construction sites crew size jobs LIMITED QUANTITY

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SPEEDING UP CALL CENTER SIMULATION AND optimization BY MARKOV CHAIN UNIFORMIZATION 08

SPEEDING UP CALL CENTER SIMULATION AND OPTIMIZATION BY MARKO...

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Winter Simulation Conference (WSC 2008)

作者： Eric Buist Wyean Chan Pierre L'Ecuyer Université de Montréal Montréal (Québec) Canada

ISBN: (纸本)9781424427086

Staffing and scheduling optimization in large multiskill call centers is time-consuming, mainly because it requires lengthy simulations to evaluate performance measures and their sensitivity. Simplified models that provide tractable formulas are unrealistic in general. In this paper we explore an intermediate solution, based on an approximate continuous-time Markov chain model of the call center. This model is more accurate than the commonly used approximations, and yet can be simulated faster than a more realistic simulation (based on non-exponential distributions and additional details). To speed up the simulation, we uniformize the Markov chain and simulate only its discrete-time version. We show how performance measures such as the fraction of calls of each type answered within a given waiting time limit can be recovered from this simulation, how to synchronize common random numbers in this setting, and how to use this in the first phase of an optimization algorithm based on the cutting plane method. We also discuss various implementation issues and provide empirical results.

关键词： simulating Call Centers Markov chain cutting plane method CHL1 gene optimization algorithms random numbers realistic simulation discrete-time Personnel Staffing and Scheduling

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AN EXPERIMENTAL STUDY OF AN ITERATIVE SIMULATION-optimization ALGORITHM FOR PRODUCTION PLANNING 08

AN EXPERIMENTAL STUDY OF AN ITERATIVE SIMULATION-OPTIMIZATIO...

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Winter Simulation Conference (WSC 2008)

作者： Durmus Fatih Irdem Necip Baris Kacar Reha Uzsoy North Carolina State University Raleigh NC

ISBN: (纸本)9781424427086

It is well known from queueing and simulation models that cycle times in capacitated production systems increase nonlinearly with resource utilization, which poses considerable difficulty for the conventional linear programming (LP) models used for this purpose. Hung and Leachman (1996) propose a highly intuitive iterative approach where a detailed simulation model of the production facility is used to estimate flow time parameters used in an LP model We examine the convergence of this method under different experimental conditions, and conclude that it is hard to determine precisely when the method converges.

关键词： production programme Simulation models optimization algorithms time cycles Queue Manufacturing Facilities Resource utilization Production systems Time parameters WWOX gene algorithms

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Hybrid Approach to the Inverse Scattering Problem by Using Ant Colony optimization and No-Sampling Linear Sampling

Hybrid Approach to the Inverse Scattering Problem by Using A...

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2008 IEEE Antennas and Propagation Society International Symposium (APSURSI 2008), vol.8

作者： M. Brignone G. Bozza A. Randazzo R. Aramini M. Piana M. Pastorino Department of Mathematics University of Genoa Genoa Italy Department of Biophysical and Electronic Engineering University of Genoa Genoa Italy Department of Computer Science University of Trento Trento Italy Department of Computer Science University of Verona Verona Italy

ISBN: (纸本)9781424420414

In the last decades, inverse scattering problems have been faced by several stochastic methods with satisfactory results, thanks to their global optimization capabilities and their ability to take into account a-priori information [1-3]. Nevertheless the computational burden required by these algorithms is often heavy. To overcome such a drawback, in this contribution a new hybrid approach is presented: a qualitative inversion technique is used to provide useful information about the location and shape of the scattering;these information are used to facilitate the convergence of a stochastic procedure, which is responsible for retrieving the point values of the dielectric permittivity. Namely, the proposed method consists of two steps: firstly the support of the scatterers is determined by the no-sampling Linear Sampling Method (nLSM), which is a fast inversion technique for visualizing the profile of a scatterer from measurements of the far-field data [4];then the dielectric parameters of interest are retrieved performing the minimization of a suitable cost function by means of an Ant Colony optimization algorithm (ACO). ACO is a recently introduced stochastic optimization algorithm, inspired by social behavior of ant colonies, to solve hard minimization problems [5,6]. In this paper the described technique will be applied to TM two-dimensional inverse scattering problems. The input data of this approach is the far-field matrix whose ij-entry is the far-field sample u{sub}∞(x{sub}i, d{sub}j) measured in the direction x{sub}i when the targets are illuminated by a plane wave impinging from direction d{sub}j.

关键词： Ant colony optimization Scattering inverse scattering Cost functions far-field optimization algorithms INVERSE SCATTERING PROBLEM ADMINISTRATIVE CONSENT ORDER Stochastic

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Optimal Radome Design with Particle Swarm optimization

Optimal Radome Design with Particle Swarm Optimization

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2008 IEEE Antennas and Propagation Society International Symposium (APSURSI 2008), vol.6

作者： Hidetoshi Chiba Yoshio Inasawa Hiroaki Miyashita Yoshihiko Konishi Mitsubishi Electric Corporation Limited Kamakura Kanagawa Japan

ISBN: (纸本)9781424420414

This paper presents the optimal radome design using optimization algorithm. Design of a radome is, in general, a formidable problem, since the design philosophy needs to take into account the arbitrariness with respect to the shape of the radome and the incidence angle of the incident wave into the radome. To circumvent this problem, optimization algorithm appears to be a powerful tool. In this article, particle swarm optimization (PSO), which has recently drawn considerable attention in a wide range of applications, is employed for the design of a radome, in which the frequency characteristics of the transmission coefficient of the radome is adopted as the objective function, and the radome wall thickness and the shape of the radome are optimized. In addition, for the PSO algorithm, we introduce a concept analogous to "mutation" in GA so as to enhance the globality of the optimal solution, and call it as MPSO (Mutated PSO). We deal with MPSO, PSO and GA, and report the comparisons and characteristics of the optimized radome.

关键词： Radomes radome design parametric subharmonic oscillator Particle swarm optimization Methylprednisolone Suleptanate design theory frequency characteristic angle of incidence Gallium optimization algorithms TRANSMISSION COEFFICIENT

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Modified Particle Swarm optimization for Search Missions

Modified Particle Swarm Optimization for Search Missions

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40th Southeastern Symposium on System Theory (SSST 2008)

作者： Ryan R. Pitre Electrical Engineering Department University of New Orleans New Orleans LA USA

ISBN: (纸本)9781424418060

There are many applications that can benefit from a well planned search. Whether the search objective is a lost hiker, a stolen vehicle on the interstate, or enemies on the battlefield, some assumptions must be made about the search objective before the search can begin. These assumptions focus the search in areas that have a relatively high likelihood of finding the targets of interest. A common approach to mission planning is to apply an optimization algorithm and obtain a good solution based on these assumptions. In general, the mission planner uses simulated targets to emulate the expected target behavior in order to evaluate candidate search paths. In practice, a major drawback is that the prior distribution of targets is only used to evaluate the search paths rather than to guide the optimization algorithm in generating the search paths. This paper introduces a method that explicitly exploits the sampled target distribution to create search paths, which naturally improves the results since the search paths directly depend on the time varying target locations. Results from a realistic cooperative path planning scenario show that explicit usage of target distributions can improve the performance of particle swarm optimization.

关键词： Particle swarm optimization search path optimization algorithms Targets Paths Searches mission planning Prior distribution Byways

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optimization of the separation of ionizable compounds in micellar electrokinetic chromatography by simultaneous change of pH and SDS concentration

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ELECTROPHORESIS 2007年第20期28卷 3712-3721页

作者： Tellez, Adolfo Fuguet, Elisabet Roses, Marti Univ Barcelona Dept Quim Anal E-08028 Barcelona Spain

A method to optimize the separation in micellar EKC (MEKC) of mixtures of acidic compounds as a function of two parameters, pH and concentration of sodium dodecyl sulfate, has been developed. The method considers the prediction of the retention time and the shape of the peaks. The retention time is predicted from the retention factor model and the peak shape by a polynomically modified Gaussian function that considers peak width, asymmetry factor, and height. An algorithm to calculate the global resolution of the separation at any experimental pH and [SDS] has been applied. This algorithm provides a 3-D resolution map to easily detect the areas in which resolution for the separation of the compounds is maximum. Initial experiments to fit the models have been performed with a set of ten phenolic compounds with different hydrophobicities and pK(a) values, and therefore, expected to behave in a different way with changes of pH and surfactant concentration. The experiments encompassed a pH range from 6.7 to 11.1, and a sodium dodecyl sulfate concentration range from 40 to 80 mM. Through the proposed methodology, chromatograms have been simulated at different pH and [SDS] very accurately. Furthermore, the resolution at any experimental point within the studied ranges have been also calculated, giving an optimum resolution value at pH 6.7 and [SDS] = 72 mM.

关键词： ionizable compounds MEKC optimization algorithms resolution simulation of chromatograms

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Satellite formation mission optimization with a multi-impulse design

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JOURNAL OF SPACECRAFT AND ROCKETS 2007年第2期44卷 425-433页

作者： Hoskins, Aaron B. Atkins, Ella M. Univ Michigan Dept Aerosp Engn Ann Arbor MI 48105 USA

Satellite formation flight has emerged as a method to increase science return and enable missions that had been impossible with a single spacecraft. Formations often must maintain a precise geometry, which complicates mission design, given natural orbit dynamics. This paper presents a multi-impulse formation design strategy that is a compromise between active control and drift solutions. This design, formulation is applied to optimize the magnetospheric multiscale tetrahedron mission using two optimization algorithms, a hierarchical strategy, and a particle swarm approach. Results are presented for a variety of multi-impulse problem specifications, including formation attitude, demonstrating that a multi-impulse solution is a viable strategy that can dramatically improve formation accuracy and longevity at minimal fuel cost. The impact of perturbing forces on optimal designs and their costs is also characterized.

关键词： formation compromise Optimal design active control orbit dynamics satellites Religious Missions optimization algorithms Longevity

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