共查询到19条相似文献,搜索用时 203 毫秒
1.
2.
在单层球壳的优化设计过程中,必然会遇到大量的不确定性信息和因素,对这些不确定性因素应该使用模糊理论加以分析和处理。同时往往要考虑多个目标如质量最小和整体刚度最大等,而各个目标之间存在矛盾,要使各个目标都达到最优很困难。采用模糊数学的原理建立单层球壳多目标模糊优化模型,通过模糊判决法,将多目标的模糊优化问题转化为单目标的非模糊优化问题,最后利用小生境遗传算法(ANGA算法)对非模糊化的优化模型进行求解。对70 m跨单层球壳进行质量、刚度模糊优化,结果令人满意,验证了该方法的合理性和可行性,说明基于ANGA算法的模糊优化方法可以有效解决优化变量繁多的大中型网格结构多目标模糊优化问题。 相似文献
3.
4.
导管架海洋平台结构模糊优化设计 总被引:7,自引:0,他引:7
考虑约束条件边界的模糊性,建立了导管架海洋平台结构模糊优化设计模型。对模糊优化模型中的设计变量、目标函数和约束条件进行了模糊处理。针对导管架海洋平台的特点,用模糊优选法确定约束条件边界容差系数,由界限搜索法求解模糊约束集和模糊目标集之交集的最优水平截集*l,进而求得模糊优化问题的最优解。以胜利油田埕北11#井采油平台为例进行了模糊优化设计,并与确定性优化设计相比较,分析了两种优化设计中设计变量的走向及原因,算例结果还显示目标函数值比确定性优化设计值有较大幅度下降,说明考虑模糊因素进行优化设计的可行性和科学性。 相似文献
5.
6.
7.
8.
9.
以工程中普遍存在的结构-声场耦合系统为研究对象,充分考虑系统本身及外载荷的不确定性,基于区间理论建立了含有非概率不确定参数的区间有限元分析方法及区间鲁棒优化模型。首先,利用区间对不确定性参数进行定量化描述,借助泰勒展式提出了求解耦合系统响应范围的区间有限元分析方法。然后,引入鲁棒优化设计的思想,基于区间序关系和区间可能度,分别建立了含区间参数目标函数和约束条件的转换模型,原区间不确定性优化问题就转化为确定性的多目标优化问题。最后通过数值算例,进一步说明了本文所建立鲁棒优化设计模型及算法的有效性。 相似文献
10.
针对武汉长江防洪模型展示大厅采用的大跨拱支预应力网壳结构,考虑优化目标函数与约束条件的模糊性,建立了该类结构体系的模糊优化设计数学模型;求解时首先通过约束水平截集法,将模糊优化模型转化为一系列确定性优化模型;然后基于拱支预应力网壳的结构特点,将预应力构件(拉索和吊杆)截面尺寸、预应力作用取值(构件初始应变)以及非预应力构件截面尺寸等优化设计变量分别归为不同的优化级别,采用分级优化思想对确定性优化模型进行求解;最后依据结构经济性与安全性平衡的目标求出结构的最优约束水平,从而得到最优的结构设计方案,并同时确定结构的合理预应力分布,由此形成了拱支预应力网壳结构的两阶段三级模糊优化设计方法。 相似文献
11.
12.
Saman Hassanzadeh Amin 《国际生产研究杂志》2013,51(5):1405-1425
In this paper, a general closed-loop supply chain (CLSC) network is configured which consists of multiple customers, parts, products, suppliers, remanufacturing subcontractors, and refurbishing sites. We propose a three-stage model including evaluation, network configuration, and selection and order allocation. In the first stage, suppliers, remanufacturing subcontractors, and refurbishing sites are evaluated based on a new quality function deployment (QFD) model. The proposed QFD model determines the relationship between customer requirements, part requirements, and process requirements. In addition, the fuzzy sets theory is utilised to overcome the uncertainty in the decision-making process. In the second stage, the closed-loop supply chain network is configured by a stochastic mixed-integer nonlinear programming model. It is supposed that demand is an uncertain parameter. Finally in the third stage, suppliers, remanufacturing subcontractors, and refurbishing sites are selected and order allocation is determined. To this end, a multi-objective mixed-integer linear programming model is presented. An illustrative example is conducted to show the process. The main novel innovation of the proposed model is to consider the CLSC network configuration and selection process simultaneously, under uncertain demand and in an uncertain decision-making environment. 相似文献
13.
14.
供应链配送中心的评价选择是供应链管理的重要课题.层次分析法(AHP)只能分析经过大量简化处理的树状结构或者其他理想结构.因此,采用解释结构模型(ISM)建立配送中心评价选择指标体系,用模糊网络分析法(FANP)进行计算分析,对以制造业为主导的供应链配送中心进行评价和选择,不仅考虑了指标的层次关系,也考虑到各层中因素之间的相互关系,解决了对具有网络关系的混合型结构评价指标体系的评价选择问题,克服了层次分析法(AHP)等传统算法的局限,在实际应用中具有很好的效果. 相似文献
15.
16.
17.
《国际生产研究杂志》2012,50(24):7567-7585
This paper solves a strategic-level decision problem on determining the optimal location of (re)manufacturers and logistics centres with the consideration of facility scales in an integrated closed-loop supply chain network. A two-stage stochastic mixed-integer non-linear programming model is established to minimise the fixed cost and the expected operation costs under uncertain demand and return. We develop an improved tabu search heuristic algorithm to solve the model. We also design a distance-based decision rule to validate the effectiveness of the proposed model. Numerical experiments are conducted to test the performance of the proposed model and the solution method. In addition, sensitivity analysis is provided to investigate the influences of varying inspection locations and recovery rates on the final performance. 相似文献
18.
19.
Deepak Sankar Somasundaram 《工程优选》2013,45(10):1043-1062
This article presents an approach to enhance the Hooke-Jeeves optimization algorithm through the use of fuzzy logic. The Hooke-Jeeves algorithm, similar to many other optimization algorithms, uses predetermined fixed parameters. These parameters do not depend on the objective function values in the current search region. In the proposed algorithm, several fuzzy logic controllers are integrated at the various stages of the algorithm to create a new optimization algorithm: Fuzzy-Controlled Hooke-Jeeves algorithm. The results of this work show that incorporating fuzzy logic in the Hooke-Jeeves algorithm can improve the ability of the algorithm to reach an extremum in different typical optimization test cases and design problems. Sensitivity analysis of the variables of the algorithm is also considered. 相似文献