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International Conference on Tools with Artificial Intelligence

作者： Sufian Sudeng Naruemon Wattanapongsakorn Department of Computer Engineering King Mongkut's University of Technology Thonburi 126 Pracha-Uthit Rd. Bangmod Toongkhru Bangkok Thailand 10140

ISBN: (纸本)9781509001644

Helping the human decision maker (DM) in finding the most preferred solution is the main purpose of Preference-based multi-objective Evolutionary Algorithm (P-MOEA). Interactive methods have been increasingly developed during the years because the preference information is less explicit than other methods. In addition, the DM can specify and correct his/her preference during the course of optimization. Our attention is to develop a new P-MOEA under the assumption that the DM must be available and willing to participate in solution process interactively. Our approach is hybridized between two well-known preference models, reference point and extended dominance approaches. Initially, pattern solution is approximated, Region of Interest (ROI) is identified by the means of user-supplied reference-point, and then a pruning mechanism called ASA approach is applied in order to filter out undesired solutions. The approach is evaluated using Component Redundancy Allocation Problem (RAP) in order to demonstrate the usefulness of our approach in practical context.

关键词： multi-objective optimization preference-based multi-objective evolutionary algorithm pareto-optimal solutions interactive approach

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GECCO'2014 tutorial on evolutionary multiobjective optimization 14

GECCO'2014 tutorial on evolutionary multiobjective optimizat...

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16th Genetic and Evolutionary Computation Conference Companion, GECCO 2014 Companion

作者： Brockhoff, Dimo Inria Lille - Nord Europe Villeneuve d'Ascq France

ISBN: (纸本)9781450328814

Many optimization problems are multiobjective in nature in the sense that multiple, conflicting criteria need to be optimized simultaneously. Due to the conflict between objectives, usually, no single optimal solution exists. Instead, the optimum corresponds to a set of so-called Pareto-optimal solutions for which no other solution has better function values in all *** multiobjective optimization (EMO) algorithms are widely used in practice for solving multiobjective optimization problems due to several reasons. As stochastic blackbox algorithms, EMO approaches allow to tackle problems with nonlinear, nondifferentiable, or noisy objective functions. As set-based algorithms, they allow to compute or approximate the full set of Pareto-optimal solutions in one algorithm run---opposed to classical solution-based techniques from the multicriteria decision making (MCDM) field. Using EMO approaches in practice has two other advantages: they allow to learn about a problem formulation, for example, by automatically revealing common design principles among (Pareto-optimal) solutions (innovization) and it has been shown that certain single-objective problems become easier to solve with randomized search heuristics if the problem is reformulated as a multiobjective one (multiobjectivization).This tutorial aims at giving a broad introduction to the EMO field and at presenting some of its recent research results in more detail. More specifically, we are going to (i) introduce the basic principles of EMO algorithms in comparison to classical solution-based approaches, (ii) show a few practical examples which motivate the use of EMO in terms of the mentioned innovization and multiobjectivization principles, and (iii) present a general overview of state-of-the-art algorithms and techniques. Moreover, we will present some of the most important research results in areas such as indicator-based EMO, preference articulation, and performance *** classifi

关键词： tutorial emo multi-criteria decision making evolutionary multiobjective optimization

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Divergence Behaviour of the Successive Geometric Mean Method of Pairwise Comparison Matrix Generation for a multiple Stage, multiple objective optimization Problem

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JOURNAL OF multi-CRITERIA DECISION ANALYSIS 2014年第3-4期21卷 197-208页

作者： Tarun, Prashant K. Chen, Victoria C. P. Corley, H. W. Missouri Western State Univ Steven L Craig Sch Business St Joseph MO 64507 USA Univ Texas Arlington Ind & Mfg Syst Engn Arlington TX 76019 USA

This paper focuses on the divergence behaviour of the successive geometric mean (SGM) method used to generate pairwise comparison matrices while solving a multiple stage, multiple objective (MSMO) optimization problem. The SGM method can be used in the matrix generation phase of our three-phase methodology to obtain pairwise comparison matrix at each stage of an MSMO optimization problem, which can be subsequently used to obtain the weight vector at the corresponding stage. The weight vectors across the stages can be used to convert an MSMO problem into a multiple stage, single objective (MSSO) problem, which can be solved using dynamic programming-based approaches. To obtain a practical set of non-dominated solutions (also referred to as Pareto optimal solutions) to the MSMO optimization problem, it is important to use a solution approach that has the potential to allow for a better exploration of the Pareto optimal solution space. To accomplish a more exhaustive exploration of the Pareto optimal solution space, the weight vectors that are used to scalarize the MSMO optimization problem into its corresponding MSSO optimization problem should vary across the stages. Distinct weight vectors across the stages are tied directly with distinct pairwise comparison matrices across the stages. A pairwise comparison matrix generation method is said to diverge if it can generate distinct pairwise comparison matrices across the stages of an MSMO optimization problem. In this paper, we demonstrate the SGM method's divergence behaviour when the three-phase methodology is used in conjunction with an augmented high-dimensional, continuous-state stochastic dynamic programming method to solve a large-scale MSMO optimization problem. Copyright (C) 2013 John Wiley & Sons, Ltd.

关键词： divergence pairwise comparison matrix analytic hierarchy process multiple stage multiple objective successive geometric mean three-phase methodology stochastic dynamic programming

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Bi-objective optimization of induction machine using interval-based interactive algorithms

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COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING 2014年第3期33卷 729-744页

作者： Samarkanov, Dmitry Gillon, Frederic Brochet, Pascal Laloy, Daniel Ecole Cent Lille Villeneuve Dascq France Ecole Cent Lille L2EP Lille France Ecole Cent Lille Lab Electrotech & Elect Puissance Lille Lille France Jeumont Elect Jeumont France

Purpose - Discrete highly constrained optimization of induction machine taking into consideration two objective functions: efficiency and total costs of production. The paper aims to discuss these issues. Design/methodology/approach - Interactive and semi-interactive interval-based optimization methods were used. Two concepts of multi-objective discrete optimization were proposed. Findings - Proposed methodology and algorithms allow decision maker (DM) participate in the process of optimal design and therefore decrease the total time of optimization process. The search procedure is straightforward and it does not require special skills of DM. Presented methods were successfully versified for the problem of optimal design with discrete variables. Research limitations/implications - Three interval algorithms suitable for inverse problems are researched and verified. It generally can be used for multi-objective problems. The dominance principles for interval boxes are showed in the paper. Proposed algorithms are based on the idea of hybridization of exact and evolutionary methods. practical implications - Proposed approaches were successfully implemented within computer-aided application which is used by manufacturer of high power induction machine. Originality/value - The concept of pareto-domination using the interval boxes can be treated as original. The paper researched several elimination rules and discusses the difference between different approaches.

关键词： Algorithms optimization Design optimization Optimal design Induction machine Iterative methods

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Holistic approaches to containership design

Holistic approaches to containership design

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International Conference on Design and Operation of Container Ships

作者： Nikolopoulos, L. Papanikolaou, A. Koutroukis, G. Sames, P. Köpke, M. Ihms, M. Harries, S. National Tech. Univ. of Athens Ship Design Laboratory Greece Research and Rule Development Germanischer Lloyd SE Germany HAPAG Lloyd Germany Ship Type Expert-Containerships Germanischer Lloyd SE Germany Friendship Systems GmbH Germany

ISBN: (纸本)9781909024274

High fuel prices, low freight rates and environmental concerns have influenced the design and operational characteristics of all types of ships. In recent years particularly container ship designs were considerably changed towards a new generation of ECO-ship designs. These designs correspond to ships with lower emissions, lower operational costs and increased competitiveness compared to traditional tonnage. This paper presents a holistic, multi-objective optimization procedure for the design of such containerships. It encompasses the development of parametric models for the optimization of medium size vessels (capacity between 3,500 and 4,000 TEU) with emphasis on the Intra-Asian trade. Fully parametric geometric modeling and design simulation techniques are employed in the framework of the CAD/CAE environment of FRIENDSHIP-Framework. They include sophisticated assessment tools for the evaluation of critical ship design attributes, such as ship's weight, stability, resistance and powering for common operational conditions. The developed multi-criteria and multi-staged optimization approach enables the effective exploration of an extended design space (with the utilization of genetic algorithms-NSGA II) targeting the minimization of the Required Freight Rate (RFR), next to the Energy Efficiency Design Index (EEDI) and additionally the minimization of ballast water carriage for the common operational conditions (zero ballast in several practical loading conditions). Further emphasis is put on enhancing ship's port efficiency to reduce time in port and consequently allow the reduction of transit speed between ports, with obvious positive effects on fuel consumption and emissions. © 2014: The Royal Institution of Naval Architects.

关键词： Energy efficiency

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Construction of Data Aggregation Tree for multi-objectives in Wireless Sensor Networks through Jump Particle Swarm optimization

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Procedia Computer Science 2014年 35卷 73-82页

作者： Yao Lu Jianping Chen Ioan Comsa Pierre Kuonen Beat Hirsbrunner Department of Informatics University of Fribourg CH-1700 Switzerland Institute of Complex Systems University of Applied Sciences of Western Switzerland CH-1705 Switzerland

As a typical data aggregation technique in wireless sensor networks, the spanning tree has the ability of reducing the data redundancy and therefore decreasing the energy consumption. However, the tree construction normally ignores some other practical application requirements, such as network lifetime, convergence time and communication interference. In this case, the way how to design a tree structure subjected to multi-objectives becomes a crucial task, which is called as multi-objective steiner tree problem (MOSTP). In view of this kind of situation, a multi-objective optimization framework is proposed, and a heuristic algorithm based on jump particle swarm optimization (JPSO) with a specific double layer encoding scheme is introduced to discover Pareto optimal solution. Furthermore, the simulation results validate the feasibility and high efficiency of the novel approach by comparison with other approaches.

关键词： Spanning Tree Data Aggregation Wireless Sensor Networks Steiner Tree multi-objective optimization PSO

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流程雁阵的多目标跟踪优化方法

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计算机与应用化学 2014年第9期31卷 1127-1132页

作者：卢爱飞黄静雯李宏光北京化工大学信息科学与技术学院北京100029

流程雁阵(Process Goose Queue,PGQ)[1]为流程系统的分解协调优化提供了一个新的方法,然而,目前PGQ方法尚存在许多不足,如简单地将个体PGQ的状态跟踪处理为单目标优化问题,这与实际流程操作不符;而多级PGQ系统优化仍采用传统的数学规划... 详细信息

流程雁阵(Process Goose Queue,PGQ)[1]为流程系统的分解协调优化提供了一个新的方法,然而,目前PGQ方法尚存在许多不足,如简单地将个体PGQ的状态跟踪处理为单目标优化问题,这与实际流程操作不符;而多级PGQ系统优化仍采用传统的数学规划方法,对模型要求苛刻且依赖于初值的选取。为此,论文提出了一个面向流程雁阵多目标跟踪的优化方法。首先对多级PGQ系统进行了结构优化,然后将NSGA-Ⅱ用于多级PGQ系统中个体PGQ的多目标优化求解,得到Pareto解集;在此基础上,将逼近理想解捧序法(TOPSIS)和扩展傅里叶幅值灵敏度分析法(EFAST)应用于个体PGQ的多目标决策,并从Pareto解集选取最优解在多级PGQ系统中逐级传递,实现流程系统的分解协调优化。仿真实例验证了方法的可行性和有效性。

关键词：流程雁阵多目标 NSGA—II TOPSIS

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Planning passive filters using NSGA II for industry applications

Planning passive filters using NSGA II for industry applicat...

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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Jandecy Cabrai Leite Ignacio Perez Abril Waterloo Ferreira Silva Anderson de Oliveira Castro Rildo de Mendonça Nogueira Manoel Socorro Santos Azevedo Galileo Technology Institute of Amazon - ITEGAM Manaus AM Brasil Central University of Las Villas Electro-energetic Studies Center Santa Clara Villa Clara Cuba Central University of Las Villas. Electro-energetic Studies Center Cuba

Passive shunt harmonic filters are a convenient means of power quality preservation as well as effective reactive power compensators. The problem formulation for the optimization of passive filters has been addressed using various approaches as a single-objective or a multi-objective optimization problem. The present paper considers a new multi-objective formulation for the multiple passive filters selection and placement problem that includes the maximization of the reactive power compensation benefits accomplished by the passive filters as reactive compensators. While previous contributions solve the multi-objective problem by the minimization of a single objective function composite by several sub-objectives, the present paper use the Non-Dominated Sorting Genetic Algorithm (NSGA - II) for solving the problem. The algorithm is capable to determine the location and configuration of each filter (type, branch number, frequency tuning and quality factor). The presented algorithm find the best solution for all the buses simultaneously using many filters and also search the reactive power distribution by branch which offers the best results. The effectiveness of the proposed procedure is tested by solving a practical example.

关键词： Power harmonic filters Passive filters Reactive power Harmonic analysis optimization Capacitors

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Design of reliable fiber-based distribution networks modeled by multi-objective combinatorial optimization

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2013年第10期26卷 1227-1242页

作者： Haidine, Abdelfatteh Tech Univ Dresden Dept Elect Engn & Informat Technol D-01062 Dresden Germany

In this work, we investigate the planning of hybrid fiber/very high bit rate digital subscriber line (HFV) access networks. This HFV variant is considered as an alternative to passive optical access network. It consists of implementing optical fibers in the access network part from the central office to the street cabinets, whereas the very high bit rate digital subscriber line technology is used in the last meter part, from street cabinets to subscribers. Firstly, we discuss the different tasks of this planning problem. We model this planning problem as a multi-objective optimization problem, where different conflicting objectives have to be optimized at the same time. We consider network costs and network reliability. This problem is solved by two different approaches: the classical single-objective optimization (SOO) and the multi-objective optimization (MOO), which is a recent optimization approach that is gaining an increasing interest in practical optimization problems. MOO solves the problem by searching for different optimal trade-offs between the optimization objectives. The performances of SOO and MOO are analyzed and compared with each other using three network instances. Copyright (c) 2012 John Wiley & Sons, Ltd.

关键词： hybrid access network network planning multi-objective optimization graph reliability evolutionary algorithm network costs

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multi-objective device selection approach for component-based automation systems

Multi-objective device selection approach for component-base...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Joern Ploennigs Matthias Lehmann Bastian Wollschlaeger Tuan Linh Mai Klaus Kabitzsch Smarter Cities Technology Center IBM Research Dublin Ireland Institute of Applied Computer Science Dresden University of Technology Dresden Germany

Composing distributed automation systems from components is challenging due to large variety and number of available components on the market. multiple criteria need to be considered such as functional coverage, price, interoperability, vendor homogeneity, and energy. The paper introduces a novel heuristic approach for selecting devices considering such criteria. The performance of the approach is compared against alternative approaches in practical relevant scenarios. The results show that the approach is able to identify good design solution candidates according to the criteria and outperforms alternative approaches in the combination of quality and computational performance.

关键词： Semantics Abstracts Temperature sensors Interoperability optimization Thermostats Temperature control

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