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practical approaches to multi-objective optimization 2004

作者： Lotov, Alexander V. Russian Academy of Sciences Dorodnicyn Computing Centre 40 Vavilova str. Moscow119991 Russia State University - Higher School of Economics Moscow Russia Lomonosov Moscow State University Russia

This paper is devoted to a Pareto frontier generation technique, which is aimed at subsequent visualization of the Pareto frontier in an interaction with the user. This technique known as the Interactive Decision Maps technique was initiated about 30 years ago. Now it is applied for decision support in both convex and non-convex decision problems in various fields, from machinery design to environmental planning. The number of conflicting criteria explored with the help of the Interactive Decision Maps technique is usually between three and seven, but some users manage to apply the technique in the case of a larger number of criteria. Here we outline the main ideas of the technique, concentrating at nonlinear problems. © 2005 Dagstuhl Seminar Proceedings. All rights reserved.

关键词： multiobjective optimization

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An Adaptive Scheme to Generate the Pareto Front Based on the Epsilon-Constraint Method

An Adaptive Scheme to Generate the Pareto Front Based on the...

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practical approaches to multi-objective optimization 2004

作者： Laumanns, Marco Thiele, Lothar Zitzler, Eckart ETH Zurich Institute for Operations Research ZurichCH-8092 Switzerland ETH Zurich Computer Engineering and Networks Laboratory ZurichCH-8092 Switzerland

This paper presents a scheme for generating the Pareto front of multiobjective optimization problems by solving a sequence of constrained single-objective problems. Since the necessity of determining the constraint value a priori can be a serious drawback of the original epsilon-constraint method, our scheme generates appropriate constraint values adaptively during the run. A simple example problem is presented where the running time (measured by the number of constrained singleobjective sub-problems to be solved) of the original epsilon-constraint method is exponential in the problem size (number of decision variables), although the size of the Pareto set grows only linearly. For our method we show that - independent of the problem or the problem size - the time complexity is O(km-1), where k is the number of Pareto-optimal solutions to be found and m the number of objectives. Using the algorithm together with a standard ILP solver for the constrained single-objective problems, the exact Pareto front is generated for the three-objective 0/1 knapsack problem with up to 100 decision variables. Links to problem instances and a reference implementation of the algorithm are provided. © 2005 Dagstuhl Seminar Proceedings. All rights reserved.

关键词： multiobjective optimization

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multiobjective optimization and multiple Constraint Handling with Evolutionary Algorithms

Multiobjective Optimization and Multiple Constraint Handling...

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practical approaches to multi-objective optimization 2004

作者： Fonseca, Carlos M. Fleming, Peter J. University of Algarve CSI - Centre for Intelligent Systems Campus de Gambelas Faro8005-139 Portugal University of Sheffield Department of Automatic Control and Systems Engineering Mappin Street Sheffield S1 3JD United Kingdom

In this talk, fitness assignment in multiobjective evolutionary algorithms is interpreted as a multi-criterion decision process. A suitable decision making framework based on goals and priorities is formulated in terms of a relational operator, characterized, and shown to encompass a number of simpler decision strategies, including constraint satisfaction, lexicographic optimization, and a form of goal programming. Then, the ranking of an arbitrary number of candidates is considered, and the effect of preference changes on the cost surface seen by an evolutionary algorithm is illustrated graphically for a simple problem. The formulation of a multiobjective genetic algorithm based on the proposed decision strategy is also discussed. Niche formation techniques are used to promote diversity among preferable candidates, and progressive articulation of preferences is shown to be possible as long as the genetic algorithm can recover from abrupt changes in the cost landscape. Finally, an application to the optimization of the low-pressure spool speed governor of a Pegasus gas turbine engine is described, which illustrates how a technique such as the multiobjective Genetic Algorithm can be applied, and exemplifies how design requirements can be refined as the algorithm runs. The two instances of the problem studied demonstrate the need for preference articulation in cases where many and highly competing objectives lead to a non-dominated set too large for a finite population to sample effectively. It is shown that only a very small portion of the non-dominated set is of practical relevance, which further substantiates the need to supply preference information to the GA. © 2005 Dagstuhl Seminar Proceedings. All rights reserved.

关键词： Genetic algorithms

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A Tutorial on Evolutionary multi-objective optimization (EMO)

A Tutorial on Evolutionary Multi-Objective Optimization (EMO...

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practical approaches to multi-objective optimization 2004

作者： Deb, Kalyanmoy Department of Mechanical Engineering Indian Institute of Technology Kanpur Kanpur208016 India

Many real-world search and optimization problems are naturally posed as nonlinear programming problems having multiple objectives. Due to lack of suitable solution techniques, such problems are artificially converted into a single-objective problem and solved. The difficulty arises because such problems give rise to a set of Pareto-optimal solutions, instead of a single optimum solution. It then becomes important to find not just one Pareto-optimal solution but as many of them as possible. Classical methods are not quite efficient in solving these problems because they require repetitive applications to find multiple Pareto-optimal solutions and in some occasions repetitive applications do not guarantee finding distinct Paretooptimal solutions. The population approach of evolutionary algorithms (EAs) allows an efficient way to find multiple Pareto-optimal solutions simultaneously in a single simulation run. In this tutorial, we discussed the following aspects related to EMO: 1. The basic differences in principle of EMO with classical methods. 2. A gentle introduction to evolutionary algorithms with simple examples. A simple method of handling constraints was also discussed. 3. The concept of domination and methods of finding non-dominated solutions in a population of solutions were discussed. 4. A brief history of the development of EMO is highlighted. 5. A number of main EMO methods (NSGA-II, SPEA and PAES) were discussed. 6. The advantage of EMO methodologies was discussed by presenting a number of case studies. They clearly showed the advantage of finding a number of Pareto-optimal solutions simultaneously. 7. Three advantages of using an EMO methodology were stressed: (a) For a better decision making (in terms of choosing a compromised solution) in the presence of multiple solutions (b) For finding important relationships among decision variables (useful in design optimization). Some case studies from engineering demonstrated the importance of such studies. (c)

关键词： Genetic programming

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Reliability allocation problem in a series-parallel system

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2005年第1期90卷 55-61页

作者： Yalaoui, A Chu, CB Châtelet, E Univ Technol Troyes ISTIT Inst Informat Sci & Technol Troyes F-10010 Troyes France

In order to improve system reliability, designers may introduce in a system different technologies in parallel. When each technology is composed of components in series, the configuration belongs to the series-parallel systems. This type of system has not been studied as much as the parallel-series architecture. There exist no methods dedicated to the reliability allocation in series-parallel systems with different technologies. We propose in this paper theoretical and practical-results for the allocation problem in a series-parallel system. Two resolution approaches are developed. Firstly, a one stage problem is studied and the results, are exploited for the multi-stages problem. A theoretical condition for obtaining the optimal allocation is developed. Since this condition is too restrictive, we secondly propose an alternative approach based on an approximated function and the results of the one-stage study. This second approach is applied to numerical examples. (C) 2004 Elsevier Ltd. All rights reserved.

关键词： reliability allocation dynamic programming optimization series-parallel system

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A novel particle swarm optimization approach for optimal reactive power dispatch 15

A novel particle swarm optimization approach for optimal rea...

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15th Power Systems Computation Conference, PSCC 2005

作者： Zhao, Bo Jiang, Quanyuan Guo, Chuangxin Cao, Yijia Department of Electrical Engineering Zhejiang University Zhejiang China

In this paper, a solution to reactive power dispatch problem with a novel particle swarm optimization approach based on multi-agent systems (MAPSO) is presented. The method integrates multi-agent system (MAS) and particle swarm optimization algorithm (PSO). An agent in MAPSO represents a particle to PSO and a candidate solution to the optimization problem. All agents live in a lattice-like environment, with each agent fixed on a lattice-point. In order to quickly obtain optimal solution, each agent competes and cooperates with its neighbors, and it can also learn by using its knowledge. Making use of these agent-agent interactions and evolution mechanism of PSO, MAPSO realizes the purpose of optimizing the value of objective function. MAPSO applied for optimal reactive power dispatch is evaluated on an IEEE 30-bus power system and a practical 118-bus power system. Simulation results show that the proposed approach converges to better solutions much faster than the earlier reported approaches. The optimization strategy is general and can be used to solve other power system optimization problems as well.

关键词： multi agent systems

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A novel response surface method for design optimization of electronic packages

A novel response surface method for design optimization of e...

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6th International Conference on Thermal, Mechanical and multi-Physics Simulation and Experiments in Micro-Electronics and Micro-Systems - EuroSimE 2005

作者： Wang, Bo Ping Han, Zhen Xue Xu, Leon Reinikainen, Tommi University of Texas Arlington Nokia Inc.

ISBN: (纸本)0780390628

The response surface method has been widely used in practical engineering design optimization problems, where the optimal searches are based on the response surfaces mimicking the physical processes or models. Sometimes the response surface method is the only practical option to be able to perform design optimization, such as simulation-based design optimization when the simulations are usually computationally expensive. In conventional approaches, the response surfaces are usually built up using a group of sampling points based on certain design of experiment schemes. The accuracy of the response surface depends largely on the number of sampling points and their distributions in the design space, as well as the approximation functions for the response surface. Currently there is no general method that could achieve the necessary accuracy of a response surface with the minimal expensive (or the number of sampling points). In this paper, a novel sequential response surface updating approach is proposed to improve the efficiency and the accuracy of simulation-based optimizations for electronic packages. It is a dynamic and adaptive approach, which starts with a small number of initial sampling points based on Halton sequence (also called Quasi Monte Carlo method), and then refines the response surface by adding more sampling points during the optimization process. This method is demonstrated with a design optimization problem of the thermo-mechanical analyses of a ceramic chip carrier assembly. A simplified thermo-mechanical model is used to perform the interfacial stress analysis of the solder bounding. The objective of is to minimize the interfacial stress by changing the bonding compliance in the specified design space. The case study indicates that, comparing with the conventional direct methods, this approach could greatly improve the computational efficiency of optimization processes with the needed accuracy for simulation-based design optimization. © 2005 IEEE.

关键词： Computer aided design

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multiSCALE optimization OF FLOW DISTRIBUTION BY CONSTRUCTAL APPROACH

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China Particuology 2005年第6期3卷 329-336页

作者： Lingai Luo Daniel Tondeur Laboratoire Optimisation de la Conception et Ing#nierie de rEnvironnement ESlGEC-University de Savoie Campus Scientifique Savoie Technolac 73376 Le Bourget-Du-Lac cedex France Laboratoire des Sciences du Genie Chimique CNRS-ENS/C 1 rue Grandvfl/e 54000 Nancy France

Constructal approach is a recent concept allowing to generate and optimize multi-scale structures, in particular, branching structures, connecting a microscopic world to a macroscopic one, from an engineer＇s point of view. Branching morphologies are found in many types of natural phenomena, and may be associated to some kind of optimization, expressing the evolutionary adaptation of natural systems to their environment, In a sense, the constructal approach tries to imitate this morphogenesis while short-cutting the trial-and-error of nature. The basic ideas underlying the constructal concept and methodology are illustrated here by the examples of fluid distribution to a multi-channel reactor, and of the design of a porous material and system for gas adsorption and storage. In usual constructal theory, a tree branching is postulated for the channels or flow-paths or conductors, usually a dichotomic tree （every branch is divided into two ＂daughters＂）. The objective function of the optimization is built from the resistances to mass or heat transport, expressed here as ＂characteristic transport times＂, and the geometric result is expressed as a shape factor of a domain. The optimized shape expresses the compromise between the mass or heat transport characteristics at adjacent scales. Under suitable assumptions, simple analytical scaling laws are found, which relate the geometric and transport properties of different scales. Some challenging geometric problems may arise when applying the constructal approach to practical situations where strong geometric constraints exist. The search for analytical solutions imposes simplifying assumptions which may be at fault, calling for less constraining approaches, for example making only weak assumptions on the branching structure. Some of these challenges are brought forward along this text.

关键词： multiscale fractal constructal optimization flow distribution

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A goal-seeking approach to capital budgeting

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Socio-Economic Planning Sciences 2005年第2期39卷 165-182页

作者： Chan, Yupo DiSalvo, Joseph P. Garrambone, Michael W. Department of Systems Engineering University of Arkansas Little Rock AR 72204-1099 2801 South University United States Richmond VA 23235 2828 Scarborough Drive United States Veridian Engineering Division General Dynamics Corporation Dayton OH 45431-1255 5200 Springfield Pike United States

This paper articulates how a goal-seeking model addresses a variation of the capital-budgeting problem. Focused toward technology modernization in the public sector, this multi-criteria optimization model explicitly considers the diverse functions of the organization. In particular, the synergism amongst the functions is modeled as a multiplicative value function. The model is solved by the "constraint reduced feasible-region method", resulting in a non-convex mathematical program that produces numerical intricacies. Linearization of the criterion (objective) functions reduces such intricacy. An Army-modernization acquisition-study was used to illustrate the proposed model, showing that its non-inferior solutions are remarkably stable. Comparison is also made with other approaches, typically formulated as goal-setting programs. The model highlights how technology acquisitions are affected as the priorities of each organizational function changes. © 2004 Elsevier Ltd. All rights reserved.

关键词： multicriteria optimization Project selection Technology modernization Value functions

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Associative parametric CAE methods in the aircraft pre-design

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AEROSPACE SCIENCE AND TECHNOLOGY 2005年第7期9卷 641-651页

作者： Ledermann, C Hanske, C Wenzel, J Ermanni, P Kelm, R ETH Ctr Struct Technol CH-8092 Zurich Switzerland Airbus Deutschland GmbH Mass Properties EGW D-21129 Hamburg Germany German Aerosp Ctr Inst Struct Mech D-38108 Braunschweig Germany

Aircraft manufacturers are facing several challenges in the pre-design of aircraft structures. This early stage of the aircraft design has a very multi-disciplinary character. Different competence centres need input data, which is at this point in time to a large extent undefined. Therefore, a large variety of specialised tools is used in order to estimate and predict the required data. If these tools are not compatible, interface problems are the consequence. A permanent improvement of the applied processes with regard to the informal value as well as the applicability remains a continuous challenge. The objective of a collaboration project between Airbus Germany GmbH, the DLR Braunschweig, and the ETH Zurich is to find new methods and approaches to improve accuracy, efficiency, and flexibility of data prediction for primary aircraft structures. The use of modern CAE systems together with the integration of finite element methods into the early pre-design process is a very promising approach [F. Bianconi, P. Conti, N. Senin, DR. Wallace, CAE systems and distributed design environments, in: XII ADM International Conference, Italy, 5-7 September, 2001 [2];M. Pellicciari, G. Barbanti, A.O. Andrisano, Functional requirements for a modern CAD system, in: XII ADM International Conference, Italy, 5-7 September, 2001 [9];T. Richter, H. Mechler, D. Schmitt, Integrated parametric aircraft design, in: ICAS 2002 Congress, Institute of Aeronautical Engineering, TU Munich]. The modular and knowledge-based architecture of modem CAE systems allows to represent complex assemblies like aircraft structures by parametric associative and very dynamic models. Design knowledge can be integrated into the modelling [M. Mantyla, S. Finger, T. Tomiyama, Knowledge Intensive CAD, vol. 2, Chapman & Hall, 1997 [8]] and different characteristics or individuals of the same structure can be mapped through parameters. This document presents concepts, which allow to design comprehensive digital model

关键词： aircraft pre-design parametric associative CAD models dynamic objects structural optimization multi-disciplinary optimisation

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