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IEEE Global Communications Conference

作者： Hongcheng Zhuang Zezhou Luo Mikhail Pikhletsky Shmelkin Dmitri Farid Khafizov Shenzhen Huawei Technologies CO. LTD. China

ISBN: (纸本)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： Dynamic Spectrum Management Fractional Frequency Reuse Inter-Cell Interference Coordination multi-objective optimization Self-Organized Networks Spectrum management inter-cell interference Self-organizing networks frequency reuse Long Term Evolution Network throughput

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multi-objective optimization algorithms for flow shop scheduling problem: a review and prospects

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2011年第5-8期55卷 723-739页

作者： Sun, Yi Zhang, Chaoyong Gao, Liang Wang, Xiaojuan Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

Since multi-objective flow shop scheduling problem (MFSP) plays a key role in practical scheduling, there has been an increasing interest in MFSP according to the literature. However, there still have been wide gaps between theories and practical applications, and the review research of multi-objective optimization algorithms in MFSP (objectives > 2) field is relatively scarce. In view of this, this paper provides a comprehensive review of both former and the state-of-the-art approaches on MFSP. Firstly, we introduce a broad description and the complexity of MFSP. Secondly, a taxonomy of multi-objective optimizations and an analysis of the publications on MFSP are presented. It is noteworthy that heuristic and meta-heuristic methods and hybrid procedures are proven much more useful than other methods in large and complex situations. Finally, future research trends and challenges in this field are proposed and analyzed. Our survey shows that algorithms developed for MFSP continues to attract significant research interest from both theoretical and practical perspectives.

关键词： Decision making Flow shop multi-objective optimization Scheduling

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multi-objective optimization of Distributed Generation Planning Using Impact Indices and Trade-off Technique

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2011年第11期39卷 1175-1190页

作者： Singh, Raj Kumar Goswami, S. K. Govt Polytech Dept Elect Engn Rampur 244901 Uttar Pradesh India Jadavpur Univ Dept Elect Engn Kolkata India

This article presents a multi-objective formulation for determining the best location and size of distributed generation. This multi-objective formulation includes reliability of service, system operational efficiency, cost of purchased energy, power quality, and system security as objective functions that are the primary concern of system planners. These objectives contradict each other and have trade-off relations. Conventional approaches for optimizing a single objective yield an uncompromised solution for such multi-objective problems. The multi-objective formulation is solved using an interactive trade-off algorithm to obtain compromised or most satisfactory non-inferior solutions. The system planner has a choice to include his/her preference on each objective through interactive steps. The practical situations, such as voltage rise phenomenon and voltage dependency of loads, are addressed, incorporating certain voltage constraints and appropriate load models. The test system is an existing Indian rural distribution network.

关键词： distributed generation distribution network optimal location optimal size multi-objective optimization

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Engine calibration: multi-objective constrained optimization of engine maps

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optimization AND ENGINEERING 2011年第3期12卷 407-424页

作者： Langouet, Hoel Metivier, Ludovic Sinoquet, Delphine Quang-Huy Tran IFP Energies Nouvelles Dept Math Appl F-92852 Rueil Malmaison France

We present two new approaches to address the optimization problem associated with engine calibration. In this area, the tuning parameters are traditionally determined in a local way, i.e., at each engine operating point, via a single-objective minimization problem. To overcome these restrictions, the first method we propose is able to cope with several objective functions simultaneously in the local formulation. The second method we put forward relies on a global formulation, which allows the whole driving cycle to be taken into account while remaining single-objective. At the practical level, the two methods are implemented by combining various existing techniques such as the LoLiMoT (Local Linear Model Tree) parameterization and the MO-CMA-ES (multi-objective Covariance Matrix Adaptation Evolution Strategy) algorithm. A better compromise appears to be achieved on real case applications.

关键词： Engine calibration Response surface LoLiMoT multi-objective optimization Evolutionary algorithm

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multi-objective optimisation and multi-criteria decision making in SLS using evolutionary approaches

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RAPID PROTOTYPING JOURNAL 2011年第6期17卷 458-478页

作者： Padhye, Nikhil Deb, Kalyanmoy MIT Cambridge MA 02139 USA IIT Kanpur Kanpur Uttar Pradesh India

Purpose - The goal of this study is to carry out multi-objective optimization by considering minimization of surface roughness (Ra) and build time (T) in selective laser sintering (SLS) process, which are functions of "build orientation". Evolutionary algorithms are applied for this purpose. The performance comparison of the optimizers is done based on statistical measures. In order to find truly optimal solutions, local search is proposed. An important task of decision making, i.e. the selection of one solution in the presence of multiple trade-off solutions, is also addressed. Analysis of optimal solutions is done to gain insight into the problem behavior. Design/methodology/approach - The minimization of Ra and T is done using two popular optimizers - multi-objective genetic algorithm (non-dominated sorting genetic algorithm (NSGA-II)) and multi-objective particle swarm optimizers (MOPSO). Standard measures from evolutionary computation - "hypervolume measure" and "attainment surface approximator" have been borrowed to compare the optimizers. Decision-making schemes are proposed in this paper based on decision theory. Findings - The objects are categorized into groups, which bear similarity in optimal solutions. NSGA-II outperforms MOPSO. The similarity of spread and convergence patterns of NSGA-II and MOPSO ensures that obtained solutions are (or are close to) Pareto-optimal set. This is validated by local search. Based on the analysis of obtained solutions, general trends for optimal orientations (depending on the geometrical features) are found. Research limitations/implications - A novel and systematic way to address multi-objective optimization decision-making post-optimal analysis is shown. Simulations utilize experimentally derived models for roughness and build time. A further step could be the experimental verification of findings provided in this study. practical implications - This study provides a thorough methodology to find optimal build orientation

关键词： multi-objective optimization Decision making Genetic algorithms Particle swarm optimization SLS

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Fundamental Performance Limits in Cross-layer Wireless optimization: Throughput, Delay, and Energy

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FOUNDATIONS AND TRENDS IN COMMUNICATIONS AND INFORMATION THEORY 2012年第1期9卷 1-112页

作者： Yeh, Edmund M. Northeastern Univ 41 Dana Res Ctr Boston MA 02115 USA

In recent years, one of the most significant developments in both the theory and practice of communication and networking has been the closer coupling between the design of physical-layer functionalities such as coding and modulation, and the design of higher-layer functionalities such as contention resolution and scheduling. This closer coupling is characteristic of the cross-layer paradigm. It is the objective of the present survey to spell out some of the basic challenges, key communication settings, and crucial results, relevant to cross-layer analysis and design for wireless systems. This work focuses primarily on communication settings relevant to wireless cellular communications, where cross-layer design principles have arguably had the greatest impact on practical systems. In order to explore the fundamental performance limits of wireless systems operating under the cross-layer paradigm, the survey shows how information theory and network theory can be leveraged to study issues such as channel modeling, coding, source burstiness, throughput, delay, multi-user interference, multi-path fading, and energy constraints in a more coherent overall analytical and design framework. The survey first examines multiaccess communication channels, the simplest example of a network setting where multiple users share a communication medium. It reviews some of the pioneering work in extending information theory to incorporate source burstiness and queueing. It then examines cross-layer design approaches for multiaccess (uplink) fading channels in wireless communications. The key concepts of stability region, throughput optimality, and delay optimality are introduced. Optimal algorithms which maximize throughput and minimize delay for multiaccess fading channels with random arrivals and queueing are characterized. Next, the survey focuses on a similar setting for communication over broadcast (downlink) fading channels, and introduce relevant results. Finally, it examines the

关键词： Surveys

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A multi-objective evolutionary optimization approach for an integrated location-inventory distribution network problem under vendor-managed inventory systems

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ANNALS OF OPERATIONS RESEARCH 2011年第1期186卷 213-229页

作者： Liao, Shu-Hsien Hsieh, Chia-Lin Lin, Yu-Siang Tamkang Univ Dept Management Sci & Decis Making Taipei 251 Taiwan Natl Taiwan Univ Sci & Technol Taiwan Tech Dept Ind Management Taipei 106 Taiwan

In this paper, we propose an integrated model to incorporate inventory control decisions-such as economic order quantity, safety stock and inventory replenishment decisions-into typical facility location models, which are used to solve the distribution network design problem. A simultaneous model is developed considering a stochastic demand, modeling also the risk poling phenomenon. multi-objective decision analysis is adopted to allow use of a performance measurement system that includes cost, customer service levels (fill rates), and flexibility (responsive level). This measurement system provides more comprehensive measurement of supply chain system performance than do traditional, single measure approaches. A multi-objective location-inventory model which permits a comprehensive trade-off evaluation for multi-objective optimization is initially presented. More specifically, a multiobjective evolutionary algorithm is developed to determine the optimal facility location portfolio and inventory control parameters in order to reach best compromise of these conflicting criteria. An experimental study using practical data was then illustrated for the possibility of the proposed approach. Computational results have presented promising solutions in solving a practical-size problem with 50 buyers and 15 potential DCs and proved to be an innovative and efficient approach for so called difficult-to-solve problems.

关键词： Supply chain integration Vendor-managed inventory multi-objective supply chain model multi-objective evolutionary algorithm

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multi-objective Evolutionary Optimisation for Product Design and Manufacturing 1

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2011年

作者： Kalyanmoy Deb (auth.), Lihui Wang, Amos H. C. Ng, Kalyanmoy Deb (eds.)

ISBN: (数字)9780857296528

ISBN: (纸本)0857296175;9780857296177

With the increasing complexity and dynamism in todays product design and manufacturing, more optimal, robust and practical approaches and systems are needed to support product design and manufacturing activities. multi-objective Evolutionary Optimisation for Product Design and Manufacturing presents a focused collection of quality chapters on state-of-the-art research efforts in multi-objective evolutionary optimisation, as well as their practical applications to integrated product design and manufacturing. multi-objective Evolutionary Optimisation for Product Design and Manufacturing consists of two major sections. The first presents a broad-based review of the key areas of research in multi-objective evolutionary optimisation. The second gives in-depth treatments of selected methodologies and systems in intelligent design and integrated manufacturing. Recent developments and innovations in multi-objective evolutionary optimisation make multi-objective Evolutionary Optimisation for Product Design and Manufacturing a useful text for a broad readership, from academic researchers to practicing engineers.

关键词： Product design Manufacturing processes Mathematical optimization

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multi-objective optimization of regenerator placement using Constraint Programming

Multi-objective optimization of regenerator placement using ...

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作者： Rumley, Sebastien Gaumier, Christian Szymanek, Radoslaw Station 11 1015 Lausanne Switzerland Station 11 1015 Lausanne Switzerland

ISBN: (纸本)9783901882425

In translucent optical networks, connections bypass most intermediate nodes transparently. However, their signal quality is affected by the traveled distance and/or the bypass operations. Hence, they might require optical-electrical-optical conversions at some intermediate nodes, in order to regenerate the carried signal. In this paper, we evaluate several approaches to deal with connection routing and regenerator placement within a translucent network. We present our Constraint Programming based multi-objective optimization model which accepts three criteria: total routing cost, total number of regeneration operations, and number of nodes performing regeneration. Our results show that this approach provides solutions in a reasonable running time for problem instances of practical interest. We discuss our method in the context of the state-of-the-art and show that optimization based on one criterion only misses the possibility to improve the solution in respect to the other aspects. © 2011 IFIP.

关键词： Regenerators

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A practical approach for cross-functional vehicle body weight optimization

A practical approach for cross-functional vehicle body weigh...

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SAE 2011 World Congress and Exhibition

作者： Deb, Anindya Chigullapalli, Anil Kumar Chou, Clifford C. Dutta, Utpal CPDM Indian Institute of Science Bangalore 560012 India Wayne State University United States Univ. of Detroit Mercy United States

The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements. The problem with performing a combined cross-functional optimization is the time associated with running such CAE algorithms that can provide a single optimal solution for heterogeneous areas such as NVH and crash safety. In the present paper, a practical MDO methodology is suggested that can be applied to weight optimization of automotive body structures by specifying constraints on frequency and crash performance. Because of the reduced number of cases to be analyzed for crash safety in comparison with other MDO approaches, the present methodology can generate a single size-optimized solution without having to take recourse to empirical techniques such as response surface-based prediction of crash performance and associated successive response surface updating for convergence. An example of weight optimization of spaceframe-based BIW of an aluminum-intensive vehicle is given to illustrate the steps involved in the current optimization process. Copyright © 2011 SAE International.

关键词： Surface properties

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