检索结果-内蒙古大学图书馆

Portland International Conference on Management of Engineering & Technology (PICMET)

作者： Choy, K. L. Ho, G. T. S. Lam, H. Y. Lin, Canhong Ng, T. W. Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781890843298

With short product life-cycles, frequent delivery schedules of products are demanded by customers. Efficient outbound logistics operations are key goals of companies wishing to maintain customer satisfaction and achieve competitive advantage. However, in current warehouse operations, order picking and loading are performed separately and products are picked manually from warehouses according to customer orders and stored temporarily in staging areas in order to fully utilize the capacity of carriers. In practice, the separation of order picking and the loading process usually results in problems of excess storage buffers, long operation time, and quality deterioration of sensitive products left in the staging area. In this paper, in order to tackle these problems, a sequential order picking and loading system (SOPLS) integrating order picking and loading processes is proposed. The Genetic Algorithm (GA) technique is adopted in the system to identify the optimum picking sequence of tours with minimal travel distance. In addition, parameter settings for GA generation are tested in the simulation to find the optimal solution. The validation of the feasibility of the proposed system is illustrated through a red wine storage scenario. By using the SOPLS in the case company, it is found that operation time for outbound logistics and product deterioration are greatly reduced.

关键词： Bufferstorage Companies Containers geneticalgorithms Loading Logistics Vehicles LOADING outbound loading Loading systems operation time Companies Power grids vehicle Logistics WAREHOUSE CONTAINERS Logistics operations order picking

来源：评论

学校读者我要写书评

暂无评论

Learning to be Risk Averse?

Learning to be Risk Averse?

引用

IEEE Conference on Computational Intelligence for Financial Engineering and Economics (CIFEr)

作者： Marks, Robert E. Univ New S Wales Econ Sydney NSW Australia Univ Melbourne Melbourne Vic 3010 Australia

ISBN: (纸本)9781479923809

The purpose of this research is to search for the best (highest performing) risk profile of agents who successively choose among risky prospects. An agent's risk profile is his attitude to perceived risk, which can vary from risk preferring to risk neutral (an expected-value decision maker) to risk averse. We use the Genetic Algorithm to search in the complex stochastic space of repeated lotteries. We find that agents with a CARA utility function learn to possess risk-neutral risk profiles. Since CARA utility functions are wealth-independent, this is not surprising. When agents have wealth-dependent, CRRA utility functions, however, they also learn to possess risk profiles that are about risk neutral (from slightly risk-averse to even slightly risk-preferring), which is surprising.

关键词： Computationalmodeling Decisionmaking Economics Educationalinstitutions geneticalgorithms Java Java Java programming language decision making economics Agents Utility functions chronic aspecific respiratory tract disease

来源：评论

学校读者我要写书评

暂无评论

Multi-Objective Optimal Design of Switched Reluctance Linear Launcher 17

Multi-Objective Optimal Design of Switched Reluctance Linear...

引用

17th IEEE International Symposium on Electromagnetic Launch Technology (EML)

作者： Song, Shoujun Zhang, Man Ge, Lefei Wang, Lusheng Northwestern Polytech Univ Sch Automat Xian 710072 Peoples R China

ISBN: (纸本)9781479927333

In this paper, based on the comparison of static electromagnetic characteristics and dynamic performances with corresponding rotating switched reluctance machine (RSRM), the original design scheme of a 1kW single-side switched reluctance linear launcher (SRLL) is obtained by traditional method. To get higher efficiency and smaller force ripple, genetic algorithm, which is improved to enhance the convergence rate and global accuracy, is applied to optimize the original design scheme. The global optimum values of key dimensions and control parameters are obtained, and the detailed structure of whole SRLL is given as well. Then, a detailed equivalent lumped parameter thermal network (LPTN) model of the considered SRLL is built, and temperature rises of some parts are got. To test the feasibility of the LPTN model, a 2-D FEM thermal model of the SRLL is built in ANSYS, and the temperature rises are obtained. The results from LPTN model match those from FEM very well. Finally, the preliminary tests of the prototype of designed SRLL are carried out and the experimental results are presented.

关键词： Electromagnetics Finiteelementanalysis geneticalgorithms Optimization Rotors Stators Torque Stators Rotors Electromagnetic fields Electromagnetism Torque XCL1 gene multi-objective optimal design Launchers Reluctance Prototype tests warming preliminary design

来源：评论

学校读者我要写书评

暂无评论

Using Equity Analyst Coverage to Determine Stock Similarity

Using Equity Analyst Coverage to Determine Stock Similarity

引用

IEEE Conference on Computational Intelligence for Financial Engineering and Economics (CIFEr)

作者： Yaros, John Robert Imielinski, Tomasz Rutgers State Univ Dept Comp Sci Piscataway NJ 08854 USA

ISBN: (纸本)9781479923809

With the observation that equity analysts tend to cover similar stocks, we propose a simple, intuitive method to convert their coverage sets into pairwise similarity values among stocks. These values are shown to have a strong positive relationship with future stock-return correlation. Further, these values are easily combined with historical correlation. Together, they produce more accurate predictions of future correlation than either does separately. Using an agglomerative clusterer and a genetic algorithm in a pipeline approach, we use the pairwise values to form clusters of similar stocks. We compare these clusters against a leading industry classification system, GICS, finding that the clusters from the combined analyst and correlation pairwise values tend to perform at least as well as GICS and often better. In an application of our pairwise values, we consider a hypothetical scenario where an investor wishes to hedge a long position in a single stock. Our results indicate that using the analyst similarity values to select a hedge portfolio leads to greater risk reduction than using GICS or hedging with a broad-market index. Using a combination of historical correlation with the analyst values leads to even greater improvements.

关键词： Clusteringalgorithms Companies Correlation geneticalgorithms Indexes Industries Pairwiseerrorprobability Companies industries Pairwise hedges Risk Reduction Coverage stocks

来源：评论

学校读者我要写书评

暂无评论

Multi-level and Multi-objective Optimization of Coilgun Considering Temperature Rise 17

Multi-level and Multi-objective Optimization of Coilgun Cons...

引用

17th IEEE International Symposium on Electromagnetic Launch Technology (EML)

作者： Tao, Xi Wang, Shuhong Huangfu, Youpeng Wang, Yuqiong Xi An Jiao Tong Univ Sch Elect Engn Xian 710049 Peoples R China Rochester Inst Technol Golisano Coll Comp & Informat Sci Rochester MN USA

ISBN: (纸本)9781479927333

The projectile of coilguns can be accelerated to a high speed due to the electromagnetic induction. The Joule losses produced by the currents in the driving coils and the projectile can't be ignored. A high temperature will weaken the mechanical strength of materials and even molten metals. In this case, the temperature rises of the driving coils and the projectile are important parameters. This paper takes the muzzle velocity and the temperature rise into account. In order to analyze the performance, the equivalent circuit model containing the calculation of the temperature rise is employed. An example is optimized with the utility of Genetic Algorithms (GA) in two levels, the velocity and the temperature. The results show that the muzzle velocity is improved and the temperature rise are conformed to the design requirements. The first stage of the prototype and the optimization are simulated by COMSOL separately in order to verify the results.

关键词： Capacitors Coilguns Coils geneticalgorithms Integratedcircuitmodeling Projectiles Prototypes

来源：评论

学校读者我要写书评

暂无评论

Genetic network parameter estimation using single and multi-objective particle swarm optimization

Genetic network parameter estimation using single and multi-...

引用

作者： Morcos, Karim M Kansas State University

学位级别：master

Multi-objective optimization problems deal with finding a set of candidate optimal solutions to be presented to the decision maker. In industry, this could be the problem of finding alternative car designs given the usually conflicting objectives of performance, safety, environmental friendliness, ease of maintenance, price among others. Despite the significance of this problem, most of the non-evolutionary algorithms which are widely used cannot find a set of diverse and nearly optimal solutions due to the huge size of the search space. At the same time, the solution set produced by most of the currently used evolutionary algorithms lacks diversity. The present study investigates a new optimization method to solve multi-objective problems based on the widely used swarm-intelligence approach, Particle Swarm Optimization (PSO). Compared to other approaches, the proposed algorithm converges relatively fast while maintaining a diverse set of solutions. The investigated algorithm, Partially Informed Fuzzy-Dominance (PIFD) based PSO uses a dynamic network topology and fuzzy dominance to guide the swarm of dominated solutions. The proposed algorithm in this study has been tested on four benchmark problems and other real-world applications to ensure proper functionality and assess overall performance. The multi-objective gene regulatory network (GRN) problem entails the minimization of the coefficient of variation of modified photothermal units (MPTUs) across multiple sites along with the total sum of similarity background between ecotypes. The results throughout the current research study show that the investigated algorithm attains outstanding performance regarding optimization aspects, and exhibits rapid convergence and diversity. Advisors/Committee Members: Sanjoy DasStephen M. Welch

关键词： ParticleSwarm Optimization Geneticnetwork Multi-objective optimization ArtificialIntelligence Evolutionary algorithms geneticalgorithms Artificial Intelligence (0800) Bioinformatics (0715) Biology Plant Physiology (0817) Computer Engineering (0464) Engineering (0537) Information Science (0723) Plant Pathology (0480) Plant Sciences (0479)

来源：评论

学校读者我要写书评

暂无评论

Methods for optimal experimental design under different cost structures: Off-line and sequential approaches

Methods for optimal experimental design under different cost...

引用

作者： Santiago Duran, Eduardo The Pennsylvania State University

学位级别：Ph.D.

An experimental design is defined by the values of the factors to be tried in a set of experimental runs. Optimal experimental design methods aim at finding a set of runs, or points in the factor space, that optimize some property of the fitted responses, a property usually related to the variance of the predictions of the response models. To get good experimental designs in practice, a large percentage of existing optimal design methods rely on a candidate list of potential experimental points from where an exchange algorithm selects a subset which is hoped to be close to the true variance optimal design. The quality of the final design depends therefore on the quality of the candidate list, and selecting the latter is not an easy task, particularly if the experimental region is irregular due to the existence of constraints. A smaller number of optimal design algorithms have been proposed based on evolutionary or genetic optimization methods in an attempt to get better local optimal designs. These methods do not rely on a candidate list of points, but have a representation of a design that is too simplistic, with the levels of the controllable factors forming a string of “genes” in this biological metaphor which does not allow to explore efficiently the very large design space. The themes of this dissertation consider the optimal design problems mentioned above. A recently proposed evolutionary algorithm, the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), is used to find experimental designs that are both [special characters omitted]- and [special characters omitted]-efficient. The ability of this algorithm to consider any non-convex, non-differentiable function composed of continuous variables makes this method an ideal global optimizer for finding experimental designs combining multiple alphabetic optimality criteria. The algorithm is applied to finding experimental designs for controllable and noise factors in the so-called Robust Parameter Design pro

关键词： optimal designs sequential optimization geneticalgorithms optimization

来源：评论

学校读者我要写书评

暂无评论

Biobjective scheduling algorithms for execution time-reliability trade-off in heterogeneous computing systems

引用

COMPUTER JOURNAL 2005年第3期48卷 300-314页

作者： Dogan, A Özgüner, F Anadolu Univ Dept Elect & Elect Engn TR-26470 Eskisehir Turkey Ohio State Univ Dept Elect Engn Columbus OH 43210 USA

A heterogeneous computing (HC) system is composed of a suite of geographically distributed high-performance machines interconnected by a high-speed network, thereby providing high-speed execution of computationally intensive applications with diverse demands. In HC systems, however, there is a possibility of machine and network failures and this can have an adverse impact on applications running on the system. In order to decrease the impact of failures on an application, matching and scheduling algorithms must be devised which minimize not only the execution time but also the failure probability of the application. However, because of the conflicting requirements, it is not possible to minimize both at the same time. Thus, the goal of this paper is to develop matching and scheduling algorithms which account for both the execution time and the failure probability and can trade off execution time against the failure probability of the application. In order to attain these goals, a biobjective scheduling problem is first formulated and then two different algorithms, the biobjective dynamic level scheduling algorithm and the biobjective genetic algorithm, are developed. Unique to both algorithms is the expression used for computing the failure probability of an application with precedence constraints. The simulation results confirm that the proposed algorithms can be used for producing task assignments where the execution time is weighed against the failure probability.

关键词： TASK-ALLOCATION MAXIMIZING RELIABILITY NETWORK RELIABILITY geneticalgorithms CONSTRAINTS

来源：评论

学校读者我要写书评

暂无评论

Exact sequence analysis for three-dimensional hydrophobic-polar lattice proteins

引用

JOURNAL OF CHEMICAL PHYSICS 2005年第11期122卷 4705-4705页

作者： Schiemann, R Bachmann, M Janke, W Univ Leipzig Inst Theoret Phys D-04109 Leipzig Germany

We have exactly enumerated all sequences and conformations of hydrophobic-polar (HP) proteins with chains of up to 19 monomers on the simple cubic lattice. For two variants of the HP model, where only two types of monomers are distinguished, we determined and statistically analyzed designing sequences, i.e., sequences that have a nondegenerate ground state. Furthermore we were interested in characteristic thermodynamic properties of HP proteins with designing sequences. In order to be able to perform these exact studies, we applied an efficient enumeration method based on contact sets. (c) 2005 American Institute of Physics.

关键词： SELF-AVOIDING WALKS MONTE-CARLO ALGORITHM FOLDING SIMULATIONS geneticalgorithms CONTACT MAPS HP MODEL SEARCH HETEROPOLYMERS THERMODYNAMICS ENUMERATION

来源：评论

学校读者我要写书评

暂无评论

Bayesian model selection applied to self-noise geoacoustic inversion

引用

JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2004年第4期116卷 2043-2056页

作者： Battle, DJ Gerstoft, P Hodgkiss, WS Kuperman, WA Nielsen, PL Scripps Inst Oceanog Marine Phys Lab La Jolla CA USA NATO Undersea Res Ctr I-19138 La Spezia Italy

Self-noise geoacoustic inversion involves the estimation of bottom parameters such as sound speeds and densities by analyzing towed-array signals whose origin is the tow platform itself. As well as forming inputs to more detailed assessments of seabed geology, these parameters enable performance predictions for sonar systems operating in shallow-water environments. In this paper, Gibbs sampling is used to obtain joint and marginal posterior probability distributions for seabed parameters. The advantages of viewing parameter estimation problems from such a probabilistic perspective include better quantified uncertainties for inverted parameters as well as the ability to compute Bayesian evidence for a range of competing geoacoustic models in order to judge which model explains the data most efficiently. (C) 2004 Acoustical Society of America.

关键词： POSTERIORI PROBABILITY-DISTRIBUTIONS OCEAN ACOUSTIC INVERSION TOW-SHIPNOISE SHALLOW-WATER SOURCE LOCALIZATION GIBBS SAMPLER QUANTIFYING UNCERTAINTY geneticalgorithms BROAD-BAND BOTTOM

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：