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Novel insights for multi-objective optimisation in engineering using Normal Boundary Intersection and (Enhanced) Normalised Normal Constraint

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STRUCTURAL AND multiDISCIPLINARY optimization 2012年第3期45卷 417-431页

作者： Logist, Filip Van Impe, Jan Katholieke Univ Leuven Chem & Biochem Proc Technol & Control BioTeC Dept Chem Engn B-3001 Louvain Belgium Katholieke Univ Leuven Optimizat Engn Ctr OPTEC Dept Chem Engn B-3001 Louvain Belgium

Normal Boundary Intersection (NBI) and (Enhanced) Normalised Normal Constraint (E)NNC are attractive and popular approaches to generate an approximation of the Pareto set in nonlinear multi-objective optimisation problems. All three methods are based on similar ideas, but do not always yield identical results, which may confuse practitioners. Hence, the current paper provides theoretical insights in the conditions under which identical results are obtained. Typically, NBI and ENNC are able to generate the same candidate Pareto points, if all additional inequalities in the ENNC subproblem are active. In general, NBI and NNC do not return the same points when three or more objectives are considered. Equivalence relations between the resulting lagrange multipliers for the additional NBI and ENNC (in) equality constraints have been derived. Moreover, the obtained relations have lead to novel criteria for detecting non-Pareto optimal points that in adverse situations maybe generated by these methods. The major advantage is that the removal criteria do not rely on a time-consuming pairwise comparison but only need matrix multiplications. A Matlab implementation has been added for completeness. The insights are illustrated for a general nonlinear bi-objective and three-objective optimisation problem, and a dynamic three-objective tubular reactor optimisation problem from chemical engineering. Finally, practical guidelines are added.

关键词： multiobjective optimization Optimal control (Enhanced) Normalized Normal Constraint Normal Boundary Intersection

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multi-attribute optimization in service selection

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WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS 2012年第1期15卷 1-31页

作者： Yu, Qi Bouguettaya, Athman Rochester Inst Technol Coll Comp & Informat Sci Rochester NY 14623 USA RMIT Sch Comp Sci & Informat Technol Melbourne Vic Australia

As multiple service providers may compete to offer the same functionality with different quality of service (e.g., latency, fee, and reputation), a key issue in service computing is selecting service providers with the best user desired quality. Existing service selection approaches mostly rely on computing a predefined objective function. When multiple quality criteria are considered, users are required to express their preference over different (and sometimes conflicting) quality attributes as numeric weights. This is a rather demanding task and an imprecise specification of the weights could miss user desired services. We propose a multi-attribute optimization approach to tackle this issue. In particular, we develop a novel concept, called service skyline, and a set of service skyline computation techniques that return a set of most interesting service providers. These providers are non-dominant in all user interested quality attributes. Thus, the service skyline ensures that the user desired providers will be included. Analytical and experimental studies justify the performance of the proposed techniques. The relative small sizes of the service skylines also make it practical for service users to make selections from them.

关键词： Web service quality of service service selection

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Probabilistic approach to multi-objective Volt/Var control of distribution system considering hybrid fuel cell and wind energy sources using Improved Shuffled Frog Leaping Algorithm

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RENEWABLE ENERGY 2012年第1期39卷 228-240页

作者： Malekpour, Ahmad Reza Tabatabaei, Sajad Niknam, Taher Islamic Azad Univ Zarghan Branch Zarghan Iran Islamic Azad Univ Mahshahr Branch Dept Elect Engn Mahshahr Iran Islamic Azad Univ Marvdasht Branch Marvdasht Iran

Deregulation and restructuring in power systems, the ever-increasing demand for electricity, and concerns about the environment are the major driving forces for using Renewable Energy Sources (RES). Recently, Wind Farms (WFs) and Fuel Cell Power Plants (FCPPs) have gained great interest by Distribution Companies (DisCos) as the most common RES. In fact, the connection of enormous RES to existing distribution networks has changed the operation of distribution systems. It also affects the Volt/Var control problem, which is one of the most important schemes in distribution networks. Due to the intermittent characteristics of WFs, distribution systems should be analyzed using probabilistic approaches rather than deterministic ones. Therefore, this paper presents a new algorithm for the multi-objective probabilistic Volt/Var control problem in distribution systems including RES. In this regard, a probabilistic load flow based on Point Estimate Method (PEM) is used to consider the effect of uncertainty in electrical power production of WFs as well as load demands. The objective functions, which are investigated here, are the total cost of power generated by WFs, FCPPs and the grid: the total electrical energy losses and the total emission produced by WFs. FCPPs and DisCos. Moreover, a new optimization algorithm based on Improved Shuffled Frog Leaping Algorithm (ISFLA) is proposed to determine the best operating point for the active and reactive power generated by WFs and FCPPs, reactive power values of capacitors, and transformers' tap positions for the next day. Using the fuzzy optimization method and max-min operator. DisCos can find solutions for different objective functions, which are optimal from economical, operational and environmental perspectives. Finally, a practical 85-bus distribution test system is used to investigate the feasibility and effectiveness of the proposed method. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Wind farms Fuel cell power plant Stochastic optimization Volt/Var control Probabilistic power flow

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Design optimization of Spoke-Type Ferrite Magnet Machines by Combined Design of Experiments and Differential Evolution Algorithms

Design Optimization of Spoke-Type Ferrite Magnet Machines by...

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International Electric Machines & Drives Conference

作者： Peng Zhang Gennadi Y. Sizov Dan M. Ionel Nabeel A.O. Demerdash Marquette University Milwaukee WI USA Regal-Beloit Corporation Grafton WI USA

In this paper, a combined design optimization method utilizing Design of Experiments (DOE) and Differential Evolution (DE) algorithms was implemented to provide practical insights in the multi-objective design optimization of a 12-slot, 8-pole, spoke-type, ferrite magnet machine, with fractional-slot concentrated windings. A robust parametric model of this type of machine is provided here. In this combined design optimization approach, the Central Composite Design (CCD) method, as one of the DOE approaches, was used to perform the variables sensitivity study, from which the significant design variables were selected and the corresponding variables ranges were defined, for the DE design optimization procedure. A Computationally Efficient-Finite Element Analysis (CE-FEA) approach was utilized to estimate the performance and characteristics of 3000 candidate designs. From the study of design objectives utilizing the pareto-set and color maps, three candidate designs with minimized losses, material cost and torque ripple were compared.

关键词： spoke-type permanent magnet machines ferrite magnet design of experiments central composite design response surface methodology differential evolution design optimization computationally efficient-finite element analysis

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Traffic-based Dynamic Spectrum Management for Inter-cell Interference Coordination in LTE Networks

Traffic-based Dynamic Spectrum Management for Inter-cell Int...

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IEEE Global Communications Conference (GLOBECOM)

作者： Zhuang, Hongcheng Luo, Zezhou Pikhletsky, Mikhail Dmitri, Shmelkin Khafizov, Farid Huawei Technol CO LTD Shenzhen Peoples R China

ISBN: (纸本)9781467309219;9781467309202

Next generation cellular networks will provide users better experiences with smaller cells, which results in high dynamics and interferences. Conventional approaches for inter-cell interference coordination (ICIC) are based on fixed frequency reuse, which wastes frequency resources. As a result, the benefit brought by ICIC is suspect in practical networks. In this paper, we tackle this problem by optimizing fractional frequency reuse (FFR) and adapting to dynamic traffic maps. We formulate this problem as a multi-KPIs (Key Performance Indicators) optimization problem and propose a traffic-based dynamic spectrum management (DSM) algorithm to reduce the call drop and block ratio (CDBR), and improve the network throughput as well. Simulation results show that the proposed scheme greatly outperforms the traditional ones.

关键词： Self-Organized Networks Inter-Cell Interference Coordination Fractional Frequency Reuse multi-objective optimization Dynamic Spectrum Management

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Procedure of specification optimization of heterogeneous robotic system

Procedure of specification optimization of heterogeneous rob...

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10th IEEE Jubilee International Symposium on Applied Machine Intelligence and Informatics, SAMI 2012

作者： Komašilovs, Vitalijs Stalidzans, Egils Department of Computer Systems Latvia University of Agriculture Jelgava Latvia

ISBN: (纸本)9781457701979

Economic benefit of an industrial company depends on forethought deployment of an industrial production system. Robotic systems are used to increase effectiveness of the production system providing variety of automation approaches. The selection of robotic system for particular mission is considered based on options available on the market. The analysis on more detailed level opens opportunity to find better solutions within the domain of heterogeneous robot systems. Authors propose a functional decomposition method that allows the optimization of specification of heterogeneous multi robot system according to defined objective function. Paper describes steps of optimization procedure and provides analysis of practical example. Achieved results are used in development of solution evaluation method using heuristic algorithms. The framework for finding best configuration of the heterogeneous multi-robot system is provided by specification optimization procedure. © 2012 IEEE.

关键词： Specifications

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practical Design optimization Techniques

Practical Design Optimization Techniques

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作者： Amit Kumar Saha The University of New South Wales

学位级别：硕士

Genetic algorithms are an attractive choice for researchers and practitioners of design optimization. Their advantages are many as compared to classical optimization approaches. However, there are a number of areas to look into so as to make them more practically relevant. This thesis describes original contributions to three such areas – Robust Design optimization, Constraint Handling and Co-Kriging. Robust design optimization using genetic algorithms is computationally ex- pensive because of the high number of function evaluations involved. Hence, it is often simply not possible to use such procedures in practice. We propose some enhancements to an existing robust design optimization algorithm by making it less resource intensive and hence more practically applicable. We study a number of Bi-objective Engineering design optimization problems to understand and demonstrate the benefits of the proposed enhancements. A highlight of this study is the robust design optimization study of an Ax- isymmetric Scramjet configuration. Next, an interesting and novel constraint handling technique based on the so-called Most probable point (of failure) is described. The proposed method is applicable to optimization problems with equality and active inequality constraints. We present the findings of the proposed approach by consid- ering a test bed of a number of Single and multi-objective optimization problems. The test bed consists of standard synthetic test problems and engineering design optimization problems. A key contribution here is the formulation of a number of multi-objective equality constrained test prob- lems. Finally, an interesting modification to Co-Kriging is proposed. Co-Kriging seeks to combine training data obtained at multiple levels of fidelity to enhance the performance of Kriging. It however introduces a number of additional hyper-parameters as compared to Kriging. Determining their optimal values is critical to obtaining a successful Co-Kriging model. A g

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Response surface approaches for large decision trees: Decision making under uncertainty

Response surface approaches for large decision trees: Decisi...

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13th European Conference on the Mathematics of Oil Recovery, ECMOR 2012

作者： Gross, H. Chevron United States

Traditionally, the connection between simulation and decision analysis is done by using simulation outputs as inputs to decision algorithms. We propose to use simulation input uncertainties directly in decision algorithms by extending existing probabilistic reservoir simulation tools (experimental design, proxy models), and existing decision analysis tools (decision trees, Pareto fronts). This approach addresses questions on field development options under uncertainty (facility sizing, completion decisions or data collection campaigns). When linking probabilistic simulation with decision analysis, three practical problems arose. First, the number of reservoir uncertainties creates huge decision trees. We solve this problem by creating composite solutions, with some branches evaluated exhaustively, and others evaluated with calibrated response surfaces. Then, assumption of independence between uncertainties, often encountered, was too restrictive for practical uses. We thus specify probabilities on all uncertainty branches. Last, we must handle multiple decision drivers and understand the consequences of decisions on several metrics. We have therefore implemented multi-objective optimization capabilities. The technique developed here extends beyond the capability of existing decision analysis and uncertainty quantification tools. Its practical value is demonstrated on two field problems, and proves useful to identify optimal decision paths.

关键词： multiobjective optimization

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optimization of forming processes

Optimization of forming processes

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14th International Conference on Metal Forming, METAL FORMING 2012

作者： Chenot, Jean-Loup Bouchard, Pierre-Olivier Fourment, Lionel Lasne, Patrice Roux, Emile CEMEF Mines ParisTech and CNRS UMR7635 B. P. 207 - F-06 904 Sophia-Antipolis France Transvalor S. A 694 av. du Dr. Maurice Donat 06255 Mougins Cedex France

ISBN: (纸本)9783514007970

In the last ten years, there is a impressive development of numerical simulation codes for metal forming processes, and their use in industry for realistic process analysis and design is more and more intensive. To-day new needs have emerged, in particular "automatic" optimization of processes, using more and more complicated criterions, in order to replace previous trial and error approaches, which appear too expensive in term of human effort. The classical integral formulation for finite element simulation of metal forming processes is briefly recalled. The main important numerical developments for efficient and reliable computation of large plastic deformation are listed. In view of structural computation, a Lemaître damage model is introduced and the basic approach for physical analysis at the micro scale is summarized. The main numerical treatments for process optimization are reviewed and compared in term of effectiveness and practical implementation. Several examples illustrate the emerging possibilities for process optimization alone, or for the optimization of the in service strength of the work-piece: forging of a crankshaft, manufacturing and test of a screw head, forming of a clinched joint, wire drawing with several criteria for multi objective optimization. © 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

关键词： Finite element method

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Improving the computational efficiency of metric-based spares algorithms

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2012年第2期219卷 324-334页

作者： Nowicki, David R. Randall, Wesley S. Ramirez-Marquez, Jose Emmanuel Stevens Inst Technol Sch Syst & Enterprises Hoboken NJ 07030 USA Univ N Texas Dept Mkt & Logist Coll Business Denton TX 76201 USA

We propose a new heuristic algorithm to improve the computational efficiency of the general class of multi-Echelon Technique for Recoverable Item Control (METRIC) problems. The objective of a METRIC-based decision problem is to systematically determine the location and quantity of spares that either maximizes the operational availability of a system subject to a budget constraint or minimizes its cost subject to an operational availability target. This type of sparing analysis has proven essential when analyzing the sustainment policies of large-scale, complex repairable systems such as those prevalent in the defense and aerospace industries. Additionally, the frequency of these sparing studies has recently increased as the adoption of performance-based logistics (PBL) has increased. PBL represents a class of business strategies that converts the recurring cost associated with maintenance, repair, and overhaul (MRO) into cost avoidance streams. Central to a PBL contract is a requirement to perform a business case analysis (BCA) and central to a BCA is the frequent need to use METRIC-based approaches to evaluate how a supplier and customer will engage in a performance based logistics arrangement where spares decisions are critical. Due to the size and frequency of the problem there exists a need to improve the efficiency of the computationally intensive METRIC-based solutions. We develop and validate a practical algorithm for improving the computational efficiency of a METRIC-based approach. The accuracy and effectiveness of the proposed algorithm are analyzed through a numerical study. The algorithm shows a 94% improvement in computational efficiency while maintaining 99.9% accuracy. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Inventory Performance based logistics Logistics Supply chain optimization Outcome based contracting

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