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evolutionary computation for automatic Web service composition: an indirect representation approach

JOURNAL OF HEURISTICS 2018年第3期24卷 425-456页

作者： da Silva, Alexandre Sawczuk Mei, Yi Ma, Hui Zhang, Mengjie Victoria Univ Wellington Sch Engn & Comp Sci POB 600 Wellington 6140 New Zealand

Web services have become increasingly popular in recent years, and they are especially suitable to the process of Web service composition, which is when several services are combined to create an application that accomplishes a more complex task. In recent years, significant research efforts have been made on developing approaches for performing Quality of Service -aware Web service composition. evolutionary computing (EC) techniques have been widely used for solving this problem, since they allow for the quality of compositions to be optimised, meanwhile also ensuring that the solutions produced have the required functionality. Existing EC-based composition approaches perform constrained optimisation to produce solutions that meet those requirements, however these constraints may hinder the effectiveness of the search. To address this issue, a novel framework based on an indirect representation is proposed in this work. The core idea is to first generate candidate service compositions encoded as sequences of services. Then, a decoding scheme is developed to transform any sequence of services into a corresponding feasible service composition. Given a service sequence, the decoding scheme builds the workflow from scratch by iteratively adding the services to proper positions of the workflow in the order of the sequence. This is beneficial because it allows the optimisation to be carried out in an unconstrained way, later enforcing functionality constraints during the decoding process. A number of encoding methods and corresponding search operators, including the PSO, GA, and GP-based methods, are proposed and tested, with results showing that the quality of the solutions produced by the proposed indirect approach is higher than that of a baseline direct representation-based approach for twelve out of the thirteen datasets considered. In particular, the method using the variable-length sequence representation has the most efficient execution time, while the fixed-leng

关键词： Web service composition QoS-aware optimisation evolutionary computation Combinatorial optimisation

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evolutionary computation and structural design: A survey of the state-of-the-art

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COMPUTERS & STRUCTURES 2005年第23-24期83卷 1943-1978页

作者： Kicinger, R Arciszewski, T De Jong, K George Mason Univ Dept Civil Environm & Infrastruct Engn Fairfax VA 22030 USA George Mason Univ Dept Comp Sci Fairfax VA 22030 USA

evolutionary computation is emerging as a new engineering computational paradigm, which may significantly change the present structural design practice. For this reason, an extensive study of evolutionary computation in the context of structural design has been conducted in the Information Technology and Engineering School at George Mason University and its results are reported here. First, a general introduction to evolutionary computation is presented and recent developments in this field are briefly described. Next, the field of evolutionary design is introduced and its relevance to structural design is explained. Further, the issue of creativity/novelty is discussed and possible ways of achieving it during a structural design process are suggested. Current research progress in building engineering systems' representations, one of the key issues in evolutionary design, is subsequently discussed. Next, recent developments in constraint-handling methods in evolutionary optimization are reported. Further, the rapidly growing field of evolutionary multiobjective optimization is presented and briefly described. An emerging subfield of coevolutionary design is subsequently introduced and its current advancements reported. Next, a comprehensive review of the applications of evolutionary computation in structural design is provided and chronologically classified. Finally, a summary of the current research status and a discussion on the most promising paths of future research are also presented. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： evolutionary computation structural design conceptual design multiobjective analysis optimization constraints computer aided design

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evolutionary computation in medicine:: an overview

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ARTIFICIAL INTELLIGENCE IN MEDICINE 2000年第1期19卷 1-23页

作者： Peña-Reyes, CA Sipper, M Swiss Fed Inst Technol Log Syst Lab IN Ecublens CH-1015 Lausanne Switzerland

The term evolutionary computation encompasses a host of methodologies inspired by natural evolution that are used to solve hard problems. This paper provides an overview of evolutionary computation as applied to problems in the medical domains. We begin by outlining the basic workings of six types of evolutionary algorithms: genetic algorithms, genetic programming, evolution strategies, evolutionary programming, classifier systems, and hybrid systems. We then describe how evolutionary algorithms are applied to solve medical problems, including diagnosis, prognosis, imaging, signal processing, planning, and scheduling. Finally, we provide an extensive bibliography, classified both according to the medical task addressed and according to the evolutionary technique used. (C) 2000 Elsevier Science B.V. All rights reserved.

关键词： evolutionary computation genetic algorithms medical applications

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evolutionary computation solutions to the circle packing problem

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SOFT COMPUTING 2016年第4期20卷 1521-1535页

作者： Flores, Juan J. Martinez, Jose Calderon, Felix Univ Michoacana Morelia Michoacan Mexico

In this work, we present an evolutionary omputation-based solution to the circle packing problem (ECPP). The circle packing problem consists of placing a set of circles into a larger containing circle without overlaps: a problem known to be NP-hard. Given the impossibility to solve this problem efficiently, traditional and heuristic methods have been proposed to solve it. A na < ve representation for chromosomes in a population-based heuristic search leads to high probabilities of violation of the problem constraints, i.e., overlapping. To convert solutions that violate constraints into ones that do not (i.e., feasible solutions), in this paper we propose two repair mechanisms. The first one considers every circle as an elastic ring and overlaps create repulsion forces that lead the circles to positions where the overlaps are resolved. The second one forms a Delaunay triangulation with the circle centers and repairs the circles in each triangle at a time, making sure repaired triangles are not modified later on. Based on the proposed repair heuristics, we present the results of the solution to the CPP problem to a set of unit circle problems (whose exact optimal solutions are known). These benchmark problems are solved using genetic algorithms, evolutionary strategies, particle swarm optimization, and differential evolution. The performance of the solutions is compared to those known solutions based on the packing density. We then perform a series of experiments to determine the performance of ECPP with non-unitary circles. First, we compare ECPP's results to those of a public competition, which stand as the world record for that particular instance of the non-unitary CPP. On a second set of experiments, we control the variance of the size of the circles. In all experiments, ECPP yields satisfactory near-optimal solutions.

关键词： Optimization Circle packing evolutionary computation Genetic algorithms evolutionary strategies Particle swarm optimization Differential evolution

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evolutionary computation-based self-supervised learning for image processing: a big data-driven approach to feature extraction and fusion for multispectral object detection

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JOURNAL OF BIG DATA 2024年第1期11卷 130页

作者： Shen, Xiaoyang Li, Haibin Shankar, Achyut Viriyasitavat, Wattana Chamola, Vinay Yanshan Univ Coll Elect Engn Qinhuangdao 066000 Hebei Peoples R China Key Lab Ind Comp Control Engn Hebei Prov Qinhuangdao 066000 Hebei Peoples R China Univ Warwick WMG Coventry England Chulalongkorn Univ Fac Commerce & Accountancy Chulalongkorn Business Sch Bangkok Thailand BITS Pilani Pilani India WMG Dept Cyber Syst Engn Coventry CV7 4AL England Chandigarh Univ Univ Ctr Res & Dev Mohali 140413 Punjab India Lovely Profess Univ Sch Comp Sci Engn Phagwara 144411 Punjab India Graph Era Deemed Be Univ Dept Comp Sci & Engn Dehra Dun 248002 India Chitkara Univ Ctr Res Impact & Outcome Rajpura Punjab India

The image object recognition and detection technology are widely used in many scenarios. In recent years, big data has become increasingly abundant, and big data-driven artificial intelligence models have attracted more and more attention. evolutionary computation has also provided a powerful driving force for the optimization and improvement of deep learning models. In this paper, we propose an image object detection method based on self-supervised and data-driven learning. Differ from other methods, our approach stands out due to its innovative use of multispectral data fusion and evolutionary computation for model optimization. Specifically, our method uniquely combines visible light images and infrared images to detect and identify image targets. Firstly, we utilize a self-supervised learning method and the AutoEncoder model to perform high-dimensional feature extraction on the two types of images. Secondly, we fuse the extracted features from the visible light and infrared images to detect and identify objects. Thirdly, we introduce a model parameter optimization method using evolutionary learning algorithms to enhance model performance. Validation on public datasets shows that our method achieves comparable or superior performance to existing methods.

关键词： evolutionary computation Self-supervised learning Image processing Big data Object detection

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evolutionary computation in structural design

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ENGINEERING WITH COMPUTERS 2000年第3-4期16卷 275-286页

作者： Murawski, K Arciszewski, T De Jong, K Mil Univ Technol Warsaw Poland George Mason Univ IT&E Sch Civil Environm & Infrastruct Engn Dept Fairfax VA 22030 USA George Mason Univ IT&E Dept Comp Sci Fairfax VA USA

The paper provides the results of preliminary research on the application of evolutionary computation to integrated structural design in,which a complex design support tool automatically conducts both conceptual and detailed design. In the paper a brief overview of the state of the art in evolutionary computation and its applications to structural design is provided. Next, Inventor 2000 is described. a unique research and structural design tool developed by the authors at George Mason University that combines an evolutionary computation component with a system for wind forces analysis, and a system for the analysis, design and optimisation of steel structures. The paper also presents the results of four structural design experiments conducted with Inventor 2000. The objective of experiments was to investigate various forms of evolutionary computation as applied to structure design. Finally, the paper provides the initial research conclusions and recommendations for further research.

关键词： conceptual design design experiments evolutionary computation integrated design paradigm Inventor 2000 structural design

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evolutionary computation of the Generalized Hesitant Fuzzy Envelopment Analysis and Its Application in the Contractor Selection of Green Building Project

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IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT 2023年第10期70卷 3622-3636页

作者： Zhou, Wei Liu, Man Xu, Zeshui Yunnan Univ Finance & Econ Business Sch Kunming 650221 Yunnan Peoples R China Sichuan Univ Business Sch Chengdu 610064 Peoples R China

The evaluation presentation and numerical weight are two key factors that can affect final results in a decision-making process. In this article, we introduce the hesitant fuzzy set and the envelopment rate calculation to address these two issues respectively. Unlike the previous decision-making approaches, the newly proposed methods in this article focus on mutual influence relationships of all alternatives and make decisions by achieving the Pareto optimality. To do this, we first define the mutual hesitant fuzzy envelopment rate (MHFER) and then propose the generalized hesitant fuzzy envelopment analysis method and its two desired properties. Based on this, we develop an evolutionary computation by introducing the ideas of cooperative equilibrium and achieving the Pareto optimality of the whole decision-making process from a global perspective. After that, we further improve the evolutionary computation by fusing some inequality constraints to make the calculated MHFERs distinguishable. Then, the modeling steps and the pseudocode algorithm of the evolutionary computation are provided for an understanding of the proposed methods. Also, the computational convergence is proven, which shows the feasibility and effectiveness of the above methods. Finally, we present an example to select a suitable contractor for a green building project and it fully demonstrates the application of the proposed models. Moreover, the comparison calculations and further analysis are also provided.

关键词： Decision making Hafnium Fuzzy sets Biological system modeling Analytical models Green buildings evolutionary computation Convergence evolutionary computation generalized hesitant fuzzy envelopment analysis (GHFEA) green building project mutual influence relationship

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evolutionary computation techniques for intrusion detection in mobile ad hoc networks

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COMPUTER NETWORKS 2011年第15期55卷 3441-3457页

作者： Sen, Sevil Clark, John A. Hacettepe Univ Bilgisayar Muhendisligi Bolumu TR-06800 Ankara Turkey Univ York Dept Comp Sci York YO10 5DD N Yorkshire England

Intrusion detection on mobile ad hoc networks (MANETs) is difficult. This is because of their dynamic nature, the lack of central points, and their highly resource-constrained nodes. In this paper we explore the use of evolutionary computation techniques, particularly genetic programming and grammatical evolution, to evolve intrusion detection programs for such challenging environments. Cognizant of the particular importance of power efficiency we analyse the power consumption of evolved programs and employ a multi-objective evolutionary algorithm to discover optimal trade-offs between intrusion detection ability and power consumption. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Mobile ad hoc networks Intrusion detection evolutionary computation Multi-objective optimisation Power-aware detection Cooperative security

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evolutionary computation approaches for real offshore wind farm layout: A case study in northern Europe

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EXPERT SYSTEMS WITH APPLICATIONS 2013年第16期40卷 6292-6297页

作者： Salcedo-Sanz, S. Gallo-Marazuela, D. Pastor-Sanchez, A. Carro-Calvo, L. Portilla-Figueras, A. Prieto, L. Univ Alcala de Henares Dept Signal Proc & Commun Alcala De Henares Spain

This paper presents the layout optimization of a real offshore wind farm in northern Europe, using evolutionary computation techniques. Different strategies for the wind farm design are tested, such as regular turbines layout or free turbines disposition with fixed number of turbines. Also, different layout quality models have been applied, in order to obtain solutions with different characteristics of high energy production and low interlink cost. In all the cases, evolutionary algorithms are developed and detailed in the paper. The experiments carried out in the real problem show that the free design with fixed number of turbines is more appropriate and obtains better quality layouts than the regular design. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Offshore wind farm design Optimal layouts evolutionary computation Real case study

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evolutionary computation and agent-based modeling: biologically-inspired approaches for understanding complex social systems

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computationAL AND MATHEMATICAL ORGANIZATION THEORY 2012年第3期18卷 356-373页

作者： Cioffi-Revilla, Claudio De Jong, Kenneth Bassett, Jeffrey K. Krasnow Inst Adv Study Ctr Social Complex 4400 Univ DrMS 6B2 Fairfax VA 22030 USA George Mason Univ Fairfax VA 22030 USA

computational social science in general, and social agent-based modeling (ABM) simulation in particular, are challenged by modeling and analyzing complex adaptive social systems with emergent properties that are hard to understand in terms of components, even when the organization of component agents is know. evolutionary computation (EC) is a mature field that provides a bio-inspired approach and a suite of techniques that are applicable to and provide new insights on complex adaptive social systems. This paper demonstrates a combined EC-ABM approach illustrated through the RebeLand model of a simple but complete polity system. Results highlight tax rates and frequency of public issue that stress society as significant features in phase transitions between stable and unstable governance regimes. These initial results suggest further applications of EC to ABM in terms of multi-population models with heterogeneous agents, multi-objective optimization, dynamic environments, and evolving executable objects for modeling social change.

关键词： Agent-based modeling Social simulation evolutionary computation MASON RebeLand model

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