A new hybrid optimization algorithm

We develop a new optimization algorithm that combines the genetic algorithm and a recently proposed global optimization algorithm called the nested partitions method. The resulting hybrid algorithm retains the global perspective of the nested partitions method and the local search capabilities of the genetic algorithm. We also present a detailed application of the new algorithm to a NP-hard product design problem and it is found empirically to outperform a pure genetic algorithm implementation, particularly for large problems.     

A comparison of global optimization algorithms applied to a ride comfort optimization problem

This study presents a comparison of global optimization algorithms applied to an industrial engineering optimization problem. Three global stochastic optimization algorithms using continuous variables, i.e. the domain elimination method, the zooming method and controlled random search, have been applied to a previously studied ride comfort optimization problem. Each algorithm is executed three times and the total number of objective function evaluations needed to locate a global optimum is averaged and used as a measure of efficiency. The results show that the zooming method, with a proposed modification, is most efficient in terms of number of objective function evaluations and ability to locate the global optimum. Each design variable is thereafter given a set of discrete values and two optimization algorithms using discrete variables, i.e. a genetic algorithm and simulated annealing, are applied to the discrete ride comfort optimization problem. The results show that the genetic algorithm is more efficient than the simulated annealing algorithm for this particular optimization problem.     

基于数论佳点集的遗传算法初始种群均匀设计

文章利用数论中的佳点集理论和方法,给出了遗传算法初始种群生成的一种具有良好多样性的均匀分布设计.通过对遗传算法机理的研究,发现初始种群的分布状态不仅直接关系到遗传算法的全局收敛性,还影响算法的搜索效率,所以对初始种群进行科学合理设定是应用遗传算法进行寻优计算的一个重要问题.基于优化设计思想,提出应用佳点集均匀设计方法确定遗传算法的初始种群.这种方法具有简单易行、种群多样性好、更适合多维情况等特点,实验结果验证了该方法可以有效地改善算法的全局收敛性,提高搜索效率.     

MPI-based parallel synchronous vector evaluated particle swarm optimization for multi-objective design optimization of composite structures

This paper presents a decentralized/peer-to-peer architecture-based parallel version of the vector evaluated particle swarm optimization (VEPSO) algorithm for multi-objective design optimization of laminated composite plates using message passing interface (MPI). The design optimization of laminated composite plates being a combinatorially explosive constrained non-linear optimization problem (CNOP), with many design variables and a vast solution space, warrants the use of non-parametric and heuristic optimization algorithms like PSO. Optimization requires minimizing both the weight and cost of these composite plates, simultaneously, which renders the problem multi-objective. Hence VEPSO, a multi-objective variant of the PSO algorithm, is used. Despite the use of such a heuristic, the application problem, being computationally intensive, suffers from long execution times due to sequential computation. Hence, a parallel version of the PSO algorithm for the problem has been developed to run on several nodes of an IBM P720 cluster. The proposed parallel algorithm, using MPI's collective communication directives, establishes a peer-to-peer relationship between the constituent parallel processes, deviating from the more common master-slave approach, in achieving reduction of computation time by factor of up to 10. Finally we show the effectiveness of the proposed parallel algorithm by comparing it with a serial implementation of VEPSO and a parallel implementation of the vector evaluated genetic algorithm (VEGA) for the same design problem.     

基于遗传算法的饲料配方设计

首先,对遗传算法作了简要阐述,鉴于遗传算法的全局并行搜索能力,提出了基于遗传算法的饲料配方设计,并在遗传算法中采用了实用有效的实数编码方案。仿真实验说明,该方法在速度和解的质量方面都达到了令人满意的效果,为复杂问题的优化提供了一种新的有效的方法。     

Optimum design of composite laminates for minimum thickness

In this study, an optimization procedure is proposed to minimize thickness (or weight) of laminated composite plates subject to in-plane loading. Fiber orientation angles and layer thickness are chosen as design variables. Direct search simulated annealing (DSA), which is a reliable global search algorithm, is used to search the optimal design. Static failure criteria are used to determine whether load bearing capacity is exceeded for a configuration generated during the optimization process. In order to avoid spurious optimal designs, both the Tsai–Wu and the maximum stress criteria are employed to check static failure. Numerical results are obtained and presented for different loading cases.     

网络负载均衡优化算法的建模与仿真

研究网络资源管理中的负载均衡与优化问题,网络资源有限且负载具有突发性,造成资源浪费。采用传统单一蚁群算法或遗传算法均存在各自不足,难以适应用网络负载变化特点,使网络资源利用率低,网络拥塞严重。为了提高网络资源利用率,使网络负载更加均衡,提出一种蚁群-遗传算法的网络负载均衡方法。首先利用遗传算法对网络负载均衡问题进行全局搜索,使网络负载均衡的解迅速处于全局最优区域解附近,然后将遗传算法的解作为蚁群算法初始信息素,进行进一步搜索,最后找到网络负载均衡的最优解。仿真结果表明,用蚁群-遗传算法提高了网络资源利用率,降低网络丢包率,提高网络整体性能。     

Optimization of composite stiffened panels subject to compression and lateral pressure using a bi-level approach

Composite stiffened panel optimization is typically a mixed discrete-continuous design problem constrained by buckling and material strength. Previous work applied a bi-level optimization strategy to the problem by decomposing the mixed problem to continuous and discrete levels to reduce the optimization search space and satisfy manufacturing constraints. A fast-running optimization package, VICONOPT, was used at the continuous optimization level where the buckling analysis was accurately and effectively performed. However, the discrete level was manually adjusted to satisfy laminate design rules. This paper develops the strategy to application on continuously long aircraft wing panels subjected to compression and lateral pressure loading. The beam-column approach used to account for lateral loading for analysis during optimization is reported. A genetic algorithm is newly developed and applied to the discrete level for automated selection of laminated designs. The results that are presented show at least 13% weight saving compared with an existing datum design.     

Mixed-integer linear programming approach for global discrete sizing optimization of frame structures

This paper focuses on discrete sizing optimization of frame structures using commercial profile catalogs. The optimization problem is formulated as a mixed-integer linear programming (MILP) problem by including the equations of structural analysis as constraints. The internal forces of the members are taken as continuous state variables. Binary variables are used for choosing the member profiles from a catalog. Both the displacement and stress constraints are formulated such that for each member limit values can be imposed at predefined locations along the member. A valuable feature of the formulation, lacking in most contemporary approaches, is that global optimality of the solution is guaranteed by solving the MILP using branch-and-bound techniques. The method is applied to three design problems: a portal frame, a two-story frame with three load cases and a multiple-bay multiple-story frame. Performance profiles are determined to compare the MILP reformulation method with a genetic algorithm.     

Optimization formulations for the maximum nonlinear buckling load of composite structures

This paper focuses on criterion functions for gradient based optimization of the buckling load of laminated composite structures considering different types of buckling behaviour. A local criterion is developed, and is, together with a range of local and global criterion functions from literature, benchmarked on a number of numerical examples of laminated composite structures for the maximization of the buckling load considering fiber angle design variables. The optimization formulations are based on either linear or geometrically nonlinear analysis and formulated as mathematical programming problems solved using gradient based techniques. The developed local criterion is formulated such it captures nonlinear effects upon loading and proves useful for both analysis purposes and as a criterion for use in nonlinear buckling optimization.     

Component allocation and supporting frame topology optimization using global search algorithm and morphing mesh

This paper proposes a stepwise structural design methodology where the component layout and the supporting frame structure is sequentially found using global search algorithm and topology optimization. In the component layout design step, the genetic algorithm is used to handle system level multiobjective problem where the optimal locations of multiple components are searched. Based on the layout design searched, a new Topology Optimization method based on Morphing Mesh technique (TOMM) is applied to obtain the frame structure topology while adjusting the component locations simultaneously. TOMM is based on the SIMP method with morphable FE mesh, and component relocation and frame design is simultaneously done using two kinds of design variables: topology design variables and morphing design variables. Two examples are studied in this paper. First, TOMM method is applied to a simple cantilever beam problem to validate the proposed design methodology and justify inclusion of morphing design variables. Then the stepwise design methodology is applied to the commercial Boeing 757 aircraft wing design problem for the optimal placement of multiple components (subsystems) and the optimal supporting frame structure around them. Additional constraint on the weight balance is included and the corresponding design sensitivity is formulated. The benefit of using the global search algorithm (genetic algorithm) is discussed in terms of finding the global optimum and independency of initial design guess. It has been proved that the proposed stepwise method can provide innovative design insight for complex modern engineering systems with multi-component structures.     

基于整车配送的多仓库开路VRPTW问题的研究与实现

以整车销售物流为背景，探讨多仓库带时窗约束的车辆路线安排问题的解决方法．提出了更为复杂的基于现实的细节性要求的多配送中心开路VRPTW问题模型，并将遗传算法产生部分解和评估完整解的优化解决方法和涌现交叉算子MX1引入到带时窗的多仓库VRP问题优化中，实现了快速全局优化．提出的开路混合配送方法有利于提高车辆满载率，降低回程空载率．同时实现了运输资源的优化配置，提高车辆利用率．计算机仿真实验证明了算法的可行性．     

基于融合算法的测试优化选择问题研究

测试优化选择是个集覆盖问题,而启发式算法是求解集覆盖问题的有效方法。文中将遗传算法、BP神经网络和模拟退火算法进行融合,提出了一种融合算法,该算法充分利用遗传算法全局搜索能力强、BP神经网络训练能力强和模拟退火算法搜索速度快的优点,既避免陷入局部最优的现象,又提高了搜索的效率和精度。该算法已应用于求解测试优化问题。实例证明,该算法能够快速有效地求得测试优化问题的最优解。     

自适应主从式并行遗传算法在区间非线性规划问题求解中的应用

讨论了区间参数非线性规划问题．通过引入决策风险因子的概念，提出了一种不确定性非线性规划的一般命题形式．为求解该命题形式，提出一种自适应主从式并行遗传算法，该算法可以满足大规模优化问题的求解实时性要求，具有全局收敛性能．相对于常规主从式并行遗传算法，该算法通过动态调整从机的计算负荷，有效地解决了从机间计算负荷不均衡分布的问题．仿真结果表明了该自适应主从式并行遗传算法的可行性．     

基于能量状态法的飞机节油轨迹优化及其遗传算法实现

研究了高高空长航时飞机基于能量状态法的节油轨迹优化方法及其遗传算法寻优实现.用能量状态概念简化飞机运动模型,应用最优控制理论进行飞机飞行性能的优化,使用遗传算法进行全局寻优,继而生成最优节油飞行轨迹,并通过Matlab程序进行仿真.仿真结果表明用遗传算法进行全局寻优,程序的寻优效率较高,仿真时间较短,得到的结果也更趋合理,节省了飞机的燃油量,缩短了爬升时间.     

区间数型多式联运路线优化问题的混合遗传算法*

多式联运路线优化问题直接关系到货物运输的费用、时间和运输质量。首先分析了多式联运路线优化问题的数学模型及虚拟运输网络图;其次,将区间数排序的思想引入适应度函数的设计中,提出了一种求解区间数型多式联运路线优化问题的混合型遗传算法,给出了染色体编码、遗传算子设计、约束判断与调整及群体多样性控制的方法;最后用示例对算法的有效性进行了验证,算法的提出可为多式联运经营者的决策提供数据参考。     

考虑强度和疲劳寿命影响的层合复合材料结构优化分析

工程应用中对复合材料轻量化的要求在不断提高,为了能够在满足工程应用对材料强度和疲劳寿命要求的同时,达到减轻结构质量的目的,研究了强度和疲劳寿命影响下的复合材料层合结构优化方法,并在此基础上提出了一种基于参数化有限元技术和改进遗传算法的复合材料层合结构优化方法。根据复合材料层合结构铺层参数属于离散型变量的特点,将遗传算法编码改为联合整数编码,并且为了能快速准确求出最优解,提出了精英保留策略、交叉和变异自适应度策略。最后,基于Visual Studio和ANSYS进行联合仿真,对所提出的方法进行验证,仿真结果表明,优化后的复合材料层合结构不仅能够满足强度和疲劳寿命的约束条件,并且其质量减少到初始质量的56.2%,优化效果明显,这表明所提出的基于参数化有限元技术和改进遗传算法的复合材料层合结构优化方法是可行的。     

基于改进遗传算法的舰载机弹药调度

舰载机弹药调度所涉及设备及限制条件多,其方案设计属于NP-hard组合优化问题。传统的基本遗传算法（SGA）求解此类问题在全局搜索和收敛方面存在不足,因而提出了改进的遗传算法。采用实值分段方式编码,保证解的可行性;在交叉和变异运算中采取精英保留策略,自适应地调整保留精英及更新“劣等”个体的数量,保证了样本多样性,同时大大加快了收敛速度;通过实例仿真实验验证了此改进遗传算法在寻求最优调度方案上的优越性。     

Optimal design of hybrid laminated composite plates with dynamic and static constraints

Optimization procedures are presented that consider the static and dynamic characteristic constraints for laminated composite plates and hybrid laminated composite plates subject to a concentrated load on the center of the plate. The design variables adopted are ply angle or ply thickness. Considered constraints are deflection, natural frequency and specific damping capacity. Using a recursive linear programming method, nonlinear optimization problems are solved, and by introducing the design scaling factor, the number of iterations is reduced significantly. Relating interactive optimization procedures with the finite element method analysis, various hybrid composite plates with arbitrary boundary conditions can be designed optimally. In the optimization procedure, verification of analysis and design of the laminated composite plates are compared with a previous paper. Various design results are presented on laminated composite plates and hybrid laminated composite plates.     

On compliance and buckling objective functions in topology optimization of snap-through problems

This paper deals with topology optimization of static geometrically nonlinear structures experiencing snap-through behaviour. Different compliance and buckling criterion functions are studied and applied for topology optimization of a point loaded curved beam problem with the aim of maximizing the snap-through buckling load. The response of the optimized structures obtained using the considered objective functions are evaluated and compared. Due to the intrinsic nonlinear nature of the problem, the load level at which the objective function is evaluated has a tremendous effect on the resulting optimized design. A well-known issue in buckling topology optimization is artificial buckling modes in low density regions. The typical remedy applied for linear buckling does not have a natural extension to nonlinear problems, and we propose an alternative approach. Some possible negative implications of using symmetry to reduce the model size are highlighted and it is demonstrated how an initial symmetric buckling response may change to an asymmetric buckling response during the optimization process. This problem may partly be avoided by not exploiting symmetry, however special requirements are needed of the analysis method and optimization formulation. We apply a nonlinear path tracing algorithm capable of detecting different types of stability points and an optimization formulation that handles possible mode switching. This is an extension into the topology optimization realm of a method developed, and used for, fiber angle optimization in laminated composite structures. We finally discuss and pinpoint some of the issues related to buckling topology optimization that remains unsolved and demands further research.