检索结果-内蒙古大学图书馆

evolution algorithms IN COMBINATORIAL OPTIMIZATION

PARALLEL COMPUTING 1988年第1期7卷 65-85页

作者： MUHLENBEIN, H GORGESSCHLEUTER, M KRAMER, O Gesellschaft für Mathematik und Datenverarbeitung mbH D-5205 St. Augustin Fed. Rep. Germany

evolution algorithms for combinatorial optimization have been proposed in the 70's. They did not have a major influence. With the availability of parallel computers, these algorithms will become more important. In this paper we discuss the dynamics of three different classes of evolution algorithms: network algorithms derived from the replicator equation, Darwinian algorithms and genetic algorithms inheriting genetic information. We present a new genetic algorithm which relies on intelligent evolution of individuals. With this algorithm, we have computed the best solution of a famous travelling salesman problem. The algorithm is inherently parallel and shows a superlinear speedup in multiprocessor systems.

关键词： combinatorial optimization Darwinian algorithm evolution algorithms genetic algorithm network algorithm superlinear speedup of a new genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Pattern recognition using evolution algorithms with fast simulated annealing

引用

PATTERN RECOGNITION LETTERS 1998年第5-6期19卷 403-413页

作者： Liu, HC Huang, JS China Inst TEchnol & Commerce Dept Mech Engn Taipei Taiwan

This paper proposes a hybrid pattern recognition system based on evolution algorithms with fast simulated annealing that can even recognize patterns deformed by the transformation caused by rotation, scaling, or translation, singly or in combination. The proposed method rests on a polygonal approximation technique, which extract appropriate feature vectors of specified dimensions characterizing a given shape. The features are utilized as inputs in a matrix's based classifier for the shape recognition. Object recognition is formulated as matching a global model graph with an input scene graph representing either a single object or several overlapping objects. A matrix is defined as matching states for the model graph and scene graph and considered the matrix as organism of evolution algorithms, where the elements of the matrix are the possible matches. The proposed algorithms start with an initial temperature and select a finite number of organisms as parents, then employ evolution algorithms to produce a new population of organisms according to evolution rules, such as selection, mutation. After those sequential generation of organisms are produced, each of which tends to produce a superior population. By repeating above procedure for a finite number, the optimal matches from organism's population can be obtained. The proposed algorithms are aimed to solve two types of problems in the evolution algorithms. First, population in the evolution can be reduced, and second, hill climbing is facilitated, thus local minimum can be escaped. In this proposed evolution fast simulated annealing (EFSA) algorithms, the Boltzmann distribution function is replaced with the Cauchy distribution in the annealing process, so the EFSA cannot only increase the annealing speed more quickly at about [1 + t]/[1 + log(1 + t)] but also have more opportunity to escape from the local. The above reason is that the wing of the Cauchy probability function has reached the deeper valley, the Boltzma

关键词： evolution algorithms object recognition simulated annealing polygonal approximation

来源：评论

学校读者我要写书评

暂无评论

A fixed point evolution algorithm based on expanded Aitken rapid iteration method for global numeric optimization

引用

MATHEMATICS AND COMPUTERS IN SIMULATION 2025年 229卷 288-303页

作者： Zhang, Qian Hu, Zhongbo Hong, Nan Su, Qinghua Yangtze Univ Sch Informat & Math Jingzhou 434000 Hubei Peoples R China

evolution algorithms based on mathematical models whose reproduction operators are derived from mathematical models are a promising branch of metaheuristic algorithms. Aitken rapid iteration method, as a fixed point iteration technique for solving nonlinear equations, performs a procedure of progressive display of a root and generates an iterative sequence that exhibits a convergent trend. Inspired by the idea that an iterative sequence gradually converges to the optimal point during the progressive display procedure of a fixed point of an equation, a fixed point evolution algorithm based on the expanded Aitken rapid iteration method (FPEea) is proposed. To develop FPEea, an expanded Aitken rapid model is first constructed. Then, three polynomials which are derived from the expanded Aitken rapid model are used as the reproduction operator of FPEea to produce offspring. The performance of FPEea is investigated on CEC2019 and CEC2020 benchmark function sets, as well as four engineering design problems. Experimental results show that FPEea is an effective and competitive algorithm compared with several classical evolution algorithms and state-of-the-art algorithms.

关键词： Expanded Aitken rapid iteration method evolution algorithms Fixed point iterative method Mathematical models

来源：评论

学校读者我要写书评

暂无评论

A subspace strategy based coevolutionary framework for constrained multimodal multiobjective optimization problems

引用

SWARM AND evolutionARY COMPUTATION 2025年 95卷

作者： Yan, Li Guo, Shunge Liang, Jing Qu, Boyang Li, Chao Yu, Kunjie Zhongyuan Univ Technol Sch Automat & Elect Engn Zhengzhou 450007 Peoples R China Zhengzhou Univ Sch Elect Engn Zhengzhou 450001 Peoples R China

Constrained multimodal multiobjective optimization problems (CMMOPs) consist of multiple equivalent constrained Pareto sets (CPSs) that have the identical constrained Pareto front (CPF). The key to solving CMMOPs lies in how to locate and retain CPSs and CPF in search spaces. Thus, this paper proposes a subspace strategy based coevolutionary framework for CMMOPs, named SCCMMO. Firstly, the subspace generation and maintenance strategy is proposed to efficiently locate multiple CPSs within the decision space. Secondly, the subspace-type perception strategy is used to exploit the feasible and infeasible information in subspaces. Finally, a coevolutionary framework is introduced to improve search efficiency. To prove the effectiveness of the algorithm, the proposed method is compared with ten state-of-the-art algorithms on seventeen benchmarks. The results demonstrate the superiority of SCCMMO in solving CMMOPs. Moreover, SCCMMO also achieves better performance on the real-world problem.

关键词： Constrained multimodal multiobjective optimization Subspace strategy Coevolution evolution algorithms

来源：评论

学校读者我要写书评

暂无评论

IoT-Driven Intelligent Scheduling Solution for Industrial Sewing Based on Real-RCPSP Model

引用

FUTURE INTERNET 2025年第2期17卷 56-56页

作者： Quoc, Huu Dang The, Loc Nguyen Quang, Truong Bui Minh, Phuong Han Thuongmai Univ Fac Econ Informat Syst & Ecommerce 79 Ho Tung Mau Hanoi 100000 Vietnam Hanoi Natl Univ Educ Fac Informat Technol 136 Xuan Thuy Hanoi 100000 Vietnam

Applying IoT systems in industrial production allows data collection directly from production lines and factories. These data are aggregated, analyzed, and converted into reports to support manufacturers. Business managers can quickly and easily grasp the situation, making timely and effective management decisions. In industrial sewing, IoT applications collect production data from sewing lines, especially from industrial sewing machines, and transmit that data to cloud-based systems. This allows businesses to analyze production situations, thereby improving management capacity. This article explores the implementation of IoT applications at industrial sewing enterprises, focusing on data collection during the production process and proposing a data structure to integrate this information into the company's MIS system enterprise. In addition, the research also considers applying the Real-RCPSP problem to support businesses in planning automatic production operations.

关键词： IoT application IoT in sewing production scheduling problem evolution algorithms intelligent planning production planning Real-RCPSP problem

来源：评论

学校读者我要写书评

暂无评论

Lower Bounds for Comparison Based evolution Strategies Using VC-dimension and Sign Patterns

引用

ALGORITHMICA 2011年第3期59卷 387-408页

作者： Fournier, Herve Teytaud, Olivier CNRS Lab PRiSM UMR 8144 F-78035 Versailles France Univ Versailles St Quentin en Yvelines F-78035 Versailles France Univ Paris Sud TAO Inria LRI UMR 8623CNRS F-91405 Orsay France

We derive lower bounds on the convergence rate of comparison based or selection based algorithms, improving existing results in the continuous setting, and extending them to non-trivial results in the discrete case. This is achieved by considering the VC-dimension of the level sets of the fitness functions;results are then obtained through the use of the shatter function lemma. In the special case of optimization of the sphere function, improved lower bounds are obtained by an argument based on the number of sign patterns.

关键词： evolution algorithms Convergence speed VC-dimension Sign patterns Sphere function

来源：评论

学校读者我要写书评

暂无评论

An evolution algorithm for noise modeling of HEMT's down to cryogenic temperatures

引用

JOURNAL OF COMPUTATIONAL ELECTRONICS 2006年第4期5卷 337-340页

作者： Caddemi, Alina Catalfamo, Francesco Donato, Nicola Univ Messina Dipartimento Fis Mat & Tecnol Fis Avanzate I-98166 Messina Italy

The implementation of an evolution Algorithm (EA) for the cryogenic noise modeling of microwave devices has been the object of the present work. Several approaches exist to treat the modeling issue as far as advanced microwave transistors are concerned. The aim of such procedures is mostly oriented to extract a linear equivalent circuit including noise performance that allows to reproduce the global device behavior in a small signal regime. In the present paper, the authors show how EA's can be employed to solve the noise modeling problem according to a black-box approach. The application refers to the simulation of the Noise Parameters of High Electron Mobility Transistors (HEMT) in the 6-18 GHz frequency range and down to cryogenic temperatures (90K) compared with experimental data. The quality of results indicates that EA techniques represent a truly alternative way to determine the microwave noise performance of HEMT devices, thus furnishing a flexible tool to support CAD of high sensitivity - ultra high speed circuits.

关键词： Noise parameters evolution algorithms HEMT Microwave modeling Cryogenic temperatures

来源：评论

学校读者我要写书评

暂无评论

Training neural networks for classification using growth probability-based evolution

引用

NEUROCOMPUTING 2008年第16-18期71卷 3493-3508页

作者： Ang, J. H. Tan, K. C. Al-Mamun, A. Natl Univ Singapore Dept Elect & Comp Engn Singapore 117576 Singapore

In this paper, a novel evolutionary algorithm (EA) based on a newly formulated parameter, i.e., growth probability (P-g) is used to evolve the near optimal weights and the number of hidden neurons in neural networks (NNs). Training NNs with growth probability based evolution (NN-GP) initializes networks with only one hidden neuron and the networks are allowed to grow until a suitable size. Growing of neurons is not restricted to one hidden neuron at a time as the optimal number of hidden neurons for the NNs might be a few neurons more than what it represents now. If this solution in the search space is far, networks have to add several number of hidden neurons. Growth rate is based on Gaussian distribution thus providing a way to escape local optima. A self-adaptive version (NN-SAGP) with the aim of evolving the growth probability in parallel with NNs during each generation is also proposed. The evolved networks are applied to widely used real-world benchmark problems. Simulation results show that the proposed approach is effective for evolving NNs with good classification accuracy and low complexity. (C) 2007 Elsevier B.V. All rights reserved.

关键词： Classification evolution algorithms Growth probability Neural networks Self-adaptive

来源：评论

学校读者我要写书评

暂无评论

A differential evolution algorithm for constrained multi-objective optimization: Initial assessment

A differential evolution algorithm for constrained multi-obj...

引用

IASTED International Conference on Artificial Intelligence and Applications

作者： Kukkonen, S Lampinen, J Lappeenranta Univ Technol Dept Informat Technol FIN-53851 Lappeenranta Finland

ISBN: (纸本)0889864047

In this paper an evolutionary Algorithm, the Differential evolution algorithm, and its extension for constrained multi-objective optimization are described. The described extension is tested with a set of five benchmark multiobjective test problems and one constrained multi-objective test problem. Control parameter values for these test problems are surveyed and recommendations for initial control parameter values are concluded. The results are compared to known global Pareto-optimal fronts and to results obtained with the Strength Pareto evolutionary Algorithm in the case of benchmark problems. Results show that the extension is well comparable to the performance of the Strength Pareto evolutionary Algorithm.

关键词： multi-objective optimization Pareto-optimization constraints evolution algorithms differential evolution

来源：评论

学校读者我要写书评

暂无评论

A MULTI-AGENT evolution ALGORITHM USED FOR INPUT SHAPING OF A REPETITIVE NON-LINEAR DYNAMIC SYSTEM

引用

BATH/ASME Symposium on Fluid Power and Motion Control

作者： Bender, Niels C. Pedersen, Henrik C. Bech, Michael M. Andersen, Torben O. Aalborg Univ Dept Energy Technol DK-9220 Aalborg Denmark

ISBN: (纸本)9780791851968

This paper explores the challenges regarding designing a heuristic control algorithm for a dynamic non-linear system with multiple inputs and outputs. The presented algorithm aims to shape the voltage input (both magnitude and timing) applied to fast switching valves in a Digital Displacement unit. This consists of multiple sub-systems, where optimal decisions must be made, based on the system design and performance criteria. In this regard good performance are defined as: low electrical energy required for switching, accurate switching timing and low plunger velocity near the seat. The proposed algorithm examines the design-space in a user-defined manner combined with stochastic decision making. The randomness of the algorithm is based on the standard deviation between located elite designs. This reveals several feasible input sequences to achieve the goal, and the optimums are benchmarked with a differential evolution algorithm. The techniques are demonstrated by simulation and the results compared showing similar performance of the optimums.

关键词： evolution algorithms Heuristic control Control of digital hydraulics Digital Displacement

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：