A surrogate assisted evolutionary optimization method with application to the transonic airfoil design

A multi-layer perceptron neural network (NN) method is used for efficient estimation of the expensive objective functions in the evolutionary optimization with the genetic algorithm (GA). The estimation capability of the NN is improved by dynamic retraining using the data from successive generations. In addition, the normal distribution of the training data variables is used to determine well-trained parts of the design space for the NN approximation. The efficiency of the method is demonstrated by two transonic airfoil design problems considering inviscid and viscous flow solvers. Results are compared with those of the simple GA and an alternative surrogate method. The total number of flow solver calls is reduced by about 40% using this fitness approximation technique, which in turn reduces the total computational time without influencing the convergence rate of the optimization algorithm. The accuracy of the NN estimation is considerably improved using the normal distribution approach compared with the alternative method.     

An effective hybrid cuckoo search and genetic algorithm for constrained engineering design optimization

This article presents an effective hybrid cuckoo search and genetic algorithm (HCSGA) for solving engineering design optimization problems involving problem-specific constraints and mixed variables such as integer, discrete and continuous variables. The proposed algorithm, HCSGA, is first applied to 13 standard benchmark constrained optimization functions and subsequently used to solve three well-known design problems reported in the literature. The numerical results obtained by HCSGA show competitive performance with respect to recent algorithms for constrained design optimization problems.     

A constrained optimization algorithm based on the simplex search method

In this article, a robust method is presented for handling constraints with the Nelder and Mead simplex search method, which is a direct search algorithm for multidimensional unconstrained optimization. The proposed method is free from the limitations of previous attempts that demand the initial simplex to be feasible or a projection of infeasible points to the nonlinear constraint boundaries. The method is tested on several benchmark problems and the results are compared with various evolutionary algorithms available in the literature. The proposed method is found to be competitive with respect to the existing algorithms in terms of effectiveness and efficiency.     

Hybrid genetic optimization for design of photonic crystal emitters

A unique hybrid-optimization technique is proposed, based on genetic algorithms (GA) and gradient descent (GD) methods, for the smart design of photonic crystal (PhC) emitters. The photonic simulation is described and the granularity of photonic crystal dimensions is considered. An innovative sliding-window method for performing local heuristic search is demonstrated. Finally, the application of the proposed method on two case studies for the design of a multi-pixel photonic crystal emitter and the design of thermal emitter in thermal photovoltaic is demonstrated. Discussion in the report includes the ability of the optimal PhC structures designed using the proposed method, to produce unprecedented high emission efficiencies of 54.5% in a significantly long wavelength region and 84.9% at significantly short wavelength region.     

压电智能连续体结构/控制一体化广义拓扑优化

对于以往较少涉及到的同时考虑结构拓扑、作动器位置与数目和控制器参数等多种优化设计变量参与的压电智能板结构的一体化优化设计问题,研究了结构/控制一体化广义拓扑优化设计的方法。提出采用基于耦合模态空间的二次型最优控制系统设计与基于遗传算法和数学形态学处理的策略进行一体化拓扑优化设计实现。数值算例的结果表明,所提方法合理、有效,能够得到清晰的结构拓扑和良好的可控性。     

结构主动控制的一体化多目标优化研究

基于Pareto多目标遗传算法提出了结构主动控制系统的一体化多目标优化设计方法,对作动器位置与主动控制器进行同步优化设计.外界激励采用平稳过滤白噪声来模拟,在状态空间下通过求解Lyapunov方程,得到结构响应和主动控制力的均方值.主动控制器采用LQG控制算法来进行设计.以结构位移和加速度均方值最大值与相应无控响应均方值的最大值之比,以及所需控制力均方值之和作为多目标同步优化的目标函数.优化过程还考虑了结构与激励参数对优化结果的影响.最后以某6层平面框架有限元模型为例进行了计算机仿真分析,结果表明所提出的主动控制系统多目标一体化优化方法简单,高效,实用,具有较好的普适性.     

变入射角度和频率时的声障板的优化设计方法

声障板是声纳设计中必不可少的声学元件。根据不同要求,合理优化声障板的材料和结构参数是声障板设计的关键。遗传算法作为一种有效的优化方法,在工程优化领域得到广泛的应用。但是由于其计算时不依赖外部信息,因此染色体的构成、编码的形式以及代价函数的选择对遗传算法性能会产生重要的影响。针对在一定入射频率范围内和一定入射角度内,反射系数保持最小且基本一致,提出了一种基于遗传算法的多层复合声障板参数的优化方法。在算法中,给出了基于传递矩阵的染色体编码和基于统计原理的代价函数。通过仿真计算,验证了算法的正确性和可靠性,分析了代价函数的改变对优化结果的影响。     

遗传算法的改进策略及其在桥梁抗震优化设计中的应用效果

本文论述了采用遗传算法进行结构优化设计时遇到的诸如计算量大、早熟收敛和边界探索不足等棘手问题,提出了三个解决对策,编制了计算程序,其在桥梁抗震代化设计中的应用效果表明,改进后的遗传算法不但提高了计算速度,而且在尽可能短的时间内找到最好的优化解。     

A diversity-enriched variant of discrete PSO applied to the design of water distribution networks

The design of water distribution networks (WDNs) is addressed by using a variant of the particle swarm optimization (PSO) algorithm. This variant, which makes use of a discrete version of PSO already considered by the authors, overcomes one of the PSO's main drawbacks, namely its difficulty in maintaining acceptable levels of population diversity and in balancing local and global searches. The performance of the variant proposed here is investigated by applying the model to solve two standard benchmark problems: the Hanoi new water distribution network and the New York Tunnel water supply system. The results obtained show considerable improvements in both convergence characteristics and the quality of the final solutions, and near-optimal results are consistently achieved at reduced computational cost.     

Microstructure optimization design methods of the forging process and applications

A microstructure optimization design method of the forging process is proposed. The optimization goal is the fine grain size and homogeneous grain distribution. The optimization object is the forging process parameters and the shape of the preform die. The grain size sub-objective function, the forgings shape sub-objective function and the whole objective function including the shape and the grain size are established, respectively. The detailed optimization steps are given. The microstructure optimization program is developed using the micro-genetic algorithm and the finite element method. Then, the upsetting process of the cylindrical billet is analyzed using a self-developed program. The forging parameters and the shape of preform die of the upsetting process are optimized respectively. The fine size and homogenous distribution of the grain can be achieved by controlling the shape of the preform die and improving the friction condition.     

Applying tabu search and simulated annealing to the optimal design of sewer networks

Optimizations of sewer network designs create complicated and highly nonlinear problems wherein conventional optimization techniques often get easily bogged down in local optima and cannot successfully address such problems. In the past decades, heuristic algorithms possessing robust and efficient global search capabilities have helped to solve continuous and discrete optimization problems and have demonstrated considerable promise. This study applied tabu search (TS) and simulated annealing (SA) to the optimization of sewer network designs. For a case study, this article used the sewer network design of a central Taiwan township, which contains significantly varied elevations, and the optimal designs from TS and SA were compared with the original official design. The results show that, in contrast with the original design's failure to satisfy the minimum flow-velocity requirements, both TS and SA achieved least-cost solutions that also fulfilled all the constraints of the design criteria. According to the average performance of 200 trials, SA outperformed TS in both robustness and efficiency for solving sewer network optimization problems.     

Reliability analysis and reliability-based design optimization of roadway horizontal curves using a first-order reliability method

This article presents reliability analysis and reliability-based optimization of roadway minimum radius design based on vehicle dynamics, mainly focusing on exit ramps and interchanges. The performance functions are formulated as failure modes of vehicle rollover and sideslip. To accurately describe the failure modes, analytical models for rollover and sideslip are derived considering nonlinear characteristics of vehicle behaviour using the commercial software TruckSim. The probability of an accident is evaluated using the first-order reliability method and numerical studies are conducted using a single-unit truck model. To propose a practical application for the study, the reliability analysis for the minimum radius recommended by American Association of State Highway and Transportation Officials is conducted. The results show that, even if there are deviations from assumed design conditions of the current design guideline, the proposed design method can guarantee given target margins of safety against rollover and sideslip. Based on the reliability analysis, reliability-based design optimization is carried out and the results indicate new recommendations for minimum radii satisfying given target reliability levels.     

新型多目标遗传算法及其在导弹射击效能优化中的应用

多目标规划是一类重要的优化模型，有着广泛的实际应用，但其求解至今仍是运筹学的一个难点．针对一般约束多目标优化问题，在设计了新的适应度函数和选择算子的基础上，提出一种新型多目标遗传算法．将其应用于导弹对集群目标射击效能优化问题，验证了算法的有效性．     

超滤分离蛋白质过程快速优化新技术及其应用

介绍了蛋白质超滤分离快速优化新技术、新方法,包括脉冲进样技术,载体相超滤技术、参数连续变化超滤技术以及在这些技术基础上建立的超滤分离快速优化新方法,克服了常规蛋白质超滤分离过程优化中存在的实验工作量大、蛋白质消耗多、费时以及费用高等缺点.利用该方法对以溶菌酶和卵清蛋白为模型蛋白质的混合体系进行了研究,筛选出合适的超滤膜...     

A system methodology for optimization design of the structural crashworthiness of a vehicle subjected to a high-speed frontal crash

The structural crashworthiness design of vehicles has become an important research direction to ensure the safety of the occupants. To effectively improve the structural safety of a vehicle in a frontal crash, a system methodology is presented in this study. The surrogate model of Online support vector regression (Online-SVR) is adopted to approximate crashworthiness criteria and different kernel functions are selected to enhance the accuracy of the model. The Online-SVR model is demonstrated to have the advantages of solving highly nonlinear problems and saving training costs, and can effectively be applied for vehicle structural crashworthiness design. By combining the non-dominated sorting genetic algorithm II and Monte Carlo simulation, both deterministic optimization and reliability-based design optimization (RBDO) are conducted. The optimization solutions are further validated by finite element analysis, which shows the effectiveness of the RBDO solution in the structural crashworthiness design process. The results demonstrate the advantages of using RBDO, resulting in not only increased energy absorption and decreased structural weight from a baseline design, but also a significant improvement in the reliability of the design.     

A hybrid methodology for enhancing reliability of large systems in conceptual design and its application to the design of a multiphase flow station

This paper presents a hybrid methodology for conceptual design of large systems with the goal of enhancing system reliability. It integrates the features of several design methodologies and maintenance planning concepts with the traditional reliability analysis. The methodology considers the temporal quality characteristic “reliability” as the main objective and determines the optimal system design. Key ideas from several design methodologies, namely axiomatic design, robust design, and the theory of inventive problem solving, have been integrated with the functional prioritization framework provided by reliability-centered maintenance. A case study of the conceptual design of a multiphase pumping station for crude oil production is presented. The methodology provides a new design tool for determining system configurations with enhanced reliability taking into account maintenance resources and variability.     

A modification of threshold accepting and its application to the quadratic assignment problem

In this paper we propose a modification of the threshold accepting heuristic by Dueck and Scheuer. Instead of using discrete threshold values a threshold function similar to the cooling schedule of simulated annealing is used. Furthermore, the number of iterations during each step of the heuristic is a function of the current and the initial threshold value. Using this scheme, we investigate the trade-off between solution quality and convergence speed on different instances of the well known quadratic assignment problem. In a second set of experiments the results of a multistart-version of TA are compared with the results of unique long runs at identical CPU-requirements to identify the better optimization strategy. Since, generally, in the literature the number of starting solutions for QAP-heuristics appears to be chosen on a rather arbitrary basis, we also highlight how varying this number influences the TA-results.This article was processed by the author using the LAT_EX style filepljour2 from Springer-Verlag.     

Estimation of the compression strength of corrugated fibreboard boxes and its application to box design using a personal computer

Many papers have been published on the compression strength of corrugated fibreboard boxes, using such formulae as Kellicut's equation and McKee's equation for the calculation. These equations, however, require known values of the strength of linerboard or corrugated fibreboard, they do not include the influence of moisture content and they are inadequate in the case of wrap-around boxes. The present author measured the mechanical properties of a large number of fibreboard boxes, and has derived a statistical formula useful for estimating the compression strength of a box based on its specifications — grade of corrugated fibreboard, size of box, type of box, printed area and moisture content. The calculation gives fairly good agreement with experimental results. The estimation technique has further been converted into a personal computer program, which renders the design of corrugated fibreboard boxes an easier task.     

A demonstration of the improved efficiency of the canonical coordinates method using nonlinear combined heat and power economic dispatch problems

Economic dispatch is the short-term determination of the optimal output from a number of electricity generation facilities to meet the system load while providing power. As such, it represents one of the main optimization problems in the operation of electrical power systems. This article presents techniques to substantially improve the efficiency of the canonical coordinates method (CCM) algorithm when applied to nonlinear combined heat and power economic dispatch (CHPED) problems. The improvement is to eliminate the need to solve a system of nonlinear differential equations, which appears in the line search process in the CCM algorithm. The modified algorithm was tested and the analytical solution was verified using nonlinear CHPED optimization problems, thereby demonstrating the effectiveness of the algorithm. The CCM methods proved numerically stable and, in the case of nonlinear programs, produced solutions with unprecedented accuracy within a reasonable time.     

一种抑制EMD端点效应新方法及其在信号特征提取中的应用

经验模式分解(EMD)的端点效应一直是困扰其工程实用性的难点问题,结合端点效应产生机理和现有的研究成果,提出了一种基于端点优化对称延拓(End Optimization Symmetric Extension,EOSE)的抑制EMD端点效应新方法.通过对信号和其包络线的偏差评价函数的最小化计算,获取最佳的信号端点值,在此基础上延拓信号的上、下包络线将最大化地逼近原始信号两端点,在EMD后续"筛选"固有模态分量(IMF)过程中抛弃两端延拓的数据,将端点效应释放到原始信号的以外.将原EMD、基于EOSE改进EMD和基于时间序列建模(ARMA)改进EMD3种方法进行对比分析,仿真和实验结果表明,基于EOSE方法抑制EMD端点效应的效果最好,能够精确提取出旋转机械振动信号的典型故障特征,运算效率较高.