检索结果-内蒙古大学图书馆

17th Asian Test Symposium (ATS 08)/9th Workshop on RTL and High Level Testing (WRTLT 08)

作者： Lo, Wan-Yu Chen, Ching-Yi Su, Chin-Lung Wu, Cheng-Wen Natl Tsing Hua Univ Dept Elect Engn Lab Reliable Comp LaRC Hsinchu 30013 Taiwan

ISBN: (纸本)9780769533964

We proposed the systematic tools, RAMSES-M and TAGS-M, for test and diagnosis algorithms evaluation and development, respectively. In addition to traditional memory fault models, the tools support the MRAM specific fault model, Write Disturbance Fault (WDF) and its specific test operation, Read-previous, which is proposed in this paper too. The concept of Weighted Fault Coverage (WFC) is introduced and adopted by RAMSES-M. Several test and diagnosis algorithms generated by the proposed tool are compared with other conventional March algorithms. The results show that the proposed algorithms have better performance for testing and diagnosis.

关键词： algorithm generation fault diagnosis magnetic random access memory (MRAM) memory testing write disturbance fault weighted fault coverage

来源：评论

学校读者我要写书评

暂无评论

Evolutionary Computation in the Era of Large Language Model: Survey and Roadmap

引用

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 2025年第2期29卷 534-554页

作者： Wu, Xingyu Wu, Sheng-Hao Wu, Jibin Feng, Liang Tan, Kay Chen Hong Kong Polytech Univ Dept Data Sci & Artificial Intelligence Hong Kong Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China

Large language models (LLMs) have not only revolutionized natural language processing but also extended their prowess to various domains, marking a significant stride toward artificial general intelligence. The interplay between LLMs and evolutionary algorithms (EAs), despite differing in objectives and methodologies, share a common pursuit of applicability in complex problems. Meanwhile, EA can provide an optimization framework for LLM's further enhancement under closed box settings, empowering LLM with flexible global search capacities. On the other hand, the abundant domain knowledge inherent in LLMs could enable EA to conduct more intelligent searches. Furthermore, the text processing and generative capabilities of LLMs would aid in deploying EAs across a wide range of tasks. Based on these complementary advantages, this article provides a thorough review and a forward-looking roadmap, categorizing the reciprocal inspiration into two main avenues: 1) LLM-enhanced EA and 2) EA-enhanced LLM. Some integrated synergy methods are further introduced to exemplify the complementarity between LLMs and EAs in diverse scenarios, including code generation, software engineering, neural architecture search, and various generation tasks. As the first comprehensive review focused on the EA research in the era of LLMs, this article provides a foundational stepping stone for understanding the collaborative potential of LLMs and EAs. The identified challenges and future directions offer guidance for researchers and practitioners to unlock the full potential of this innovative collaboration in propelling advancements in optimization and artificial intelligence. We have created a GitHub repository to index the relevant papers: https://***/wuxingyu-ai/LLM4EC.

关键词： Optimization Closed box Reviews Evolutionary computation Codes Search problems Collaboration Surveys Software engineering Prompt engineering algorithm generation evolutionary algorithm (EA) large language model (LLM) neural architecture search (NAS) optimization problem prompt engineering

来源：评论

学校读者我要写书评

暂无评论

Leveraging Large Language Models for the generation of Novel Metaheuristic Optimization algorithms

Leveraging Large Language Models for the Generation of Novel...

引用

Genetic and Evolutionary Computation Conference (GECCO)

作者： Pluhacek, Michal Kazikova, Anezka Kadavy, Tomas Viktorin, Adam Senkerik, Roman Tomas Bata Univ Zlin Zlin Czech Republic

ISBN: (纸本)9798400701207

In this paper, we investigate the potential of using Large Language Models (LLMs) such as GPT-4 to generate novel hybrid swarm intelligence optimization algorithms. We use the LLM to identify and decompose six well-performing swarm algorithms for continuous optimization: Particle Swarm Optimization (PSO), Cuckoo Search (CS), Artificial Bee Colony (ABC), Grey Wolf Optimizer (GWO), Self-Organizing Migrating algorithm (SOMA), and Whale Optimization algorithm (WOA). We leverage GPT-4 to propose a hybrid algorithm that combines the strengths of these techniques for two distinct use-case scenarios. Our focus is on the process itself and various challenges that emerge during the use of GPT-4 to fulfill a series of set tasks. Furthermore, we discuss the potential impact of LLM-generated algorithms in the metaheuristics domain and explore future research directions.

关键词： Large Language Models Metaheuristic Optimization Swarm algorithms algorithm generation Decomposition and Construction GPT-4

来源：评论

学校读者我要写书评

暂无评论

Automatic generation of Optimization algorithms for Production Lot-Sizing Problems

Automatic Generation of Optimization Algorithms for Producti...

引用

IEEE Congress on Evolutionary Computation (IEEE CEC)

作者： Pessoa, Luis Filipe de Araujo Hellingrath, Bernd de Lima Neto, Fernando Buarque Univ Munster WWU Munster Germany Univ Pernambuco UPE Recife PE Brazil

ISBN: (纸本)9781728121536

Successful applications of heuristic-based methods are able to find high-quality solutions for complex problems in a feasible timeframe. However, they are usually tailored towards the problem instances under consideration and any changes in the underlying problem structure might require a redesign of the algorithm, which is expensive and very time-consuming. This paper presents results of an automatic algorithm-generation approach used to find good-performing optimization methods for the multi-level capacitated lotsizing problem, a relevant and hard combinatorial problem in production planning. A new template for generating algorithms is proposed for enabling the generation of different hybridizations between genetic algorithm-components and mathematical heuristics. Several experiments are carried out to evaluate the ability of the proposed method to generate competitive algorithms for benchmark instances, under consideration of different functions set and cutoff times. Results indicate that the method is able to generate heuristic algorithms that find high-quality solutions significantly faster than the compared human-designed algorithm.

关键词： Hyper-heuristics algorithm generation Genetic Programming Mathematical Heuristics Lot-sizing Problem

来源：评论

学校读者我要写书评

暂无评论

From a domain analysis to the specification and detection of code and design smells

引用

FORMAL ASPECTS OF COMPUTING 2010年第3-4期22卷 345-361页

作者： Moha, Naouel Gueheneuc, Yann-Gael Le Meur, Anne-Francoise Duchien, Laurence Tiberghien, Alban Univ Montreal Ptidej Team GEODES DIRO Montreal PQ Canada Univ Sci & Technol Lille CNRS LIFL UMR 8022 Adam TeamINRIA Lille Nord Europe Villeneuve Dascq France Ecole Polytech Montreal Ptidej Team DGIGL Montreal PQ Canada INRIA Rennes Bretagne Atlantique Triskell Team IRISA F-35042 Rennes France

Code and design smells are recurring design problems in software systems that must be identified to avoid their possible negative consequences on development and maintenance. Consequently, several smell detection approaches and tools have been proposed in the literature. However, so far, they allow the detection of predefined smells but the detection of new smells or smells adapted to the context of the analysed systems is possible only by implementing new detection algorithms manually. Moreover, previous approaches do not explain the transition from specifications of smells to their detection. Finally, the validation of the existing approaches and tools has been limited on few proprietary systems and on a reduced number of smells. In this paper, we introduce an approach to automate the generation of detection algorithms from specifications written using a domain-specific language. This language is defined from a thorough domain analysis. It allows the specification of smells using high-level domain-related abstractions. It allows the adaptation of the specifications of smells to the context of the analysed systems. We specify 10 smells, generate automatically their detection algorithms using templates, and validate the algorithms in terms of precision and recall on Xerces v2.7.0 and GanttProject v1.10.2, two open-source object-oriented systems. We also compare the detection results with those of a previous approach, iPlasma.

关键词： Design smells Antipatterns Code smells Domain-specific language algorithm generation Detection Java

来源：评论

学校读者我要写书评

暂无评论

A Novel Context-Free Grammar to Guide the Construction of Particle Swarm Optimization algorithms 5

A Novel Context-Free Grammar to Guide the Construction of Pa...

引用

5th Brazilian Conference on Intelligent Systems (BRACIS)

作者： Miranda, Pericles B. C. Prudencio, Ricardo B. C. Univ Fed Pernambuco Recife PE Brazil

ISBN: (纸本)9781509035663

Particle Swarm Optimization algorithm (PSO) has been largely studied over the years due to its flexibility and competitive results in different applications. Nevertheless, its performance depends on different aspects of design (e.g., inertia factor, velocity equation, topology). The task of deciding which is the best algorithm design to solve a particular problem is challenging due to the great number of possible variations and parameters to take into account. This work proposes a novel context-free grammar for Grammar-Guided Genetic Programming (GGGP) algorithms to guide the construction of Particle Swarm Optimizers. The proposed grammar addresses four aspects of the PSO algorithm that may strongly influence on its convergence: swarm initialization, neighborhood topology, velocity update equation and mutation operator. To evaluate this approach, a GGGP algorithm was set with the proposed grammar and applied to optimize the PSO algorithm in 32 unconstrained continuous optimization problems. In the experiments, we compared the designs generated considering the proposed grammar with the designs produced by other grammars proposed in the literature to automate PSO designs. The results obtained by the proposed grammar were better than the counterparts. Besides, we also compared the generated algorithms to state-of-art algorithms. The results have shown that the algorithms produced from the grammar achieved competitive results.

关键词： Particle Swarm Optimization Genetic Programming algorithm generation

来源：评论

学校读者我要写书评

暂无评论

Tree-based Grammar Genetic Programming to Evolve Particle Swarm algorithms 5

Tree-based Grammar Genetic Programming to Evolve Particle Sw...

引用

5th Brazilian Conference on Intelligent Systems (BRACIS)

作者： Miranda, Pericles B. C. Prudencio, Ricardo B. C. Univ Fed Pernambuco Recife PE Brazil

ISBN: (纸本)9781509035663

Particle Swarm Optimization (PSO) is largely used to solve optimization problems effectively. Nonetheless, the PSO performance depends on the fine tuning of different parameters. To make the algorithm design process more independent from human intervention, some researchers have treated this task as an optimization problem. Grammar-guided Genetic Programming algorithms (GGGP), in special, have been widely studied and applied in the context of algorithm optimization. GGGP algorithms produce customized designs based on a set of production rules defined in the grammar;differently from methods that simply select designs in a pre-defined limited search space. In this work, we proposed a tree-based GGGP technique for the generation of PSO algorithms. This paper intends to investigate whether this approach can improve the production of PSO algorithms when compared to other GGGP techniques already used to solve the current problem. In the experiments, a comparison between the tree-based and the commonly used linearized GGGP approach for the generation of PSO algorithms was performed. The results showed that the tree-based GGGP produced better algorithms than the counterparts. We also compared the algorithms generated by the tree-based technique to state-of-art optimization algorithms, and the results showed that the algorithms produced by the tree-based GGGP achieved competitive results.

关键词： Particle Swarm Optimization Genetic Programming algorithm generation

来源：评论

学校读者我要写书评

暂无评论

Cooperative Mobile Robotic Platforms for Wireless Control Applications

Cooperative Mobile Robotic Platforms for Wireless Control Ap...

引用

10th International Conference on Electronics, Computer and Computation (ICECCO)

作者： Papoutsidakis, Michail Piromalis, Dimitrios Chamilothoris, George Technol Inst Piraeus Dept Automat Athens 12244 Greece

ISBN: (纸本)9781479933433

The field of mobile robot tracking is active and vibrant, with more great systems and ideas being developed continuously. Exact knowledge of the position of a vehicle is a fundamental problem in mobile robot applications. In search for a solution, researchers and engineers have developed a variety of systems, sensors, and techniques for mobile robot positioning. This paper provides an implementation of tracking a hand-on robotic platform from another autonomous robot almost at the same size, which will be referred as the 'chase-hunter' application. The proposed alignment control algorithm has the advantage that can be implemented on very simple robots that lack complex sensing capabilities to detect random obstacles and the orientation of their pair robot. Low cost, though modern and up to date technology was used and all gear data will be explained in details as well as the performing scenario.

关键词： swarm robotics multitasking platforms wireless communication path tracking algorithm generation

来源：评论

学校读者我要写书评

暂无评论

Cartesian Genetic Programming Hyper-Heuristic with Parameter Configuration for Production Lot-Sizing

Cartesian Genetic Programming Hyper-Heuristic with Parameter...

引用

IEEE Congress on Evolutionary Computation (CEC) as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Pessoa, Luis Filipe de Araujo Hellingrath, Bernd Neto, Fernando Buarque de Lima Univ Munster WWU Munster Germany Univ Pernambuco UPE Recife PE Brazil

ISBN: (数字)9781728169293

ISBN: (纸本)9781728169293

The design of well-performing heuristic-based algorithms is a tedious and time-consuming task. For this purpose, several approaches to automate the algorithm design have been investigated over the last years. Among them, Genetic Programming based Hyper-Heuristics (GPHH) are able to design algorithms of varying lengths and permutations of algorithm's operators. Although the parametrization of generated algorithms is crucial for further adaptation of its behavior to the underlying problems, it has been neglected or only considered to a limited extent in many applications of GPHHs. This work proposes a way to integrate GPHH with parameter configuration. In particular, a Cartesian Genetic Programming Hyper-Heuristic (CGPHH) is developed. The proposed method is applied to the multi-level capacitated production lot-sizing problem, a complex and relevant problem in production planning. Conducted experiments evaluate both its efficacy and the quality of the generated algorithms. Finally, results are compared to the CGPHH without parameter configuration and a human-designed algorithm, indicating the ability of CGPHH-PC to generate algorithms that have the best overall-performance for different cutoff times.

关键词： Hyper-heuristics Genetic Programming algorithm generation Parameter Configuration Lot-sizing Problem

来源：评论

学校读者我要写书评

暂无评论

A domain analysis to specify design defects and generate detection algorithms

引用

11th International Conference on Fundamental Approaches to Software Engineering

作者： Moha, Naouel Gueheneuc, Yann-Gael Le Meur, Anne-Francoise Duchien, Laurence Univ Montreal Quebec City PQ Canada Univ Sci & Tech Lille INRIA LIFL Adam Team Lille France

ISBN: (纸本)9783540787426

Quality experts often need to identify in software systems design defects, which are recurring design problems, that hinder development and maintenance. Consequently, several defect detection approaches and tools have been proposed in the literature. However, we are not aware of any approach that defines and reifies the process of generating detection algorithms from the existing textual descriptions of defects. In this paper, we introduce an approach to automate the generation of detection algorithms from specifications written using a domain-specific language. The domain-specific is defined from a thorough domain analysis. We specify several design defects, generate automatically detection algorithms using templates, and validate the generated detection algorithms in terms of precision and recall on XERCES v2.7.0, an open-source object-oriented system.

关键词： design defects antipatterns code smells domain-specific language algorithm generation detection Java

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：