共查询到20条相似文献,搜索用时 445 毫秒
1.
Ali Rıza Yıldız 《The International Journal of Advanced Manufacturing Technology》2009,40(5-6):617-628
This paper presents a novel optimization approach that is a new hybrid optimization approach based on the particle swarm optimization algorithm and receptor editing property of immune system. The aim of the present research is to develop a new optimization approach and then to apply it in the solution of optimization problems in both the design and manufacturing areas. A single-objective test problem, tension spring problem, pressure vessel design optimization problem taken from the literature and two case studies for multi-pass turning operations are solved by the proposed new hybrid approach to evaluate performance of the approach. The results obtained by the proposed approach for the case studies are compared with a hybrid genetic algorithm, scatter search algorithm, genetic algorithm, and integration of simulated annealing and Hooke-Jeeves pattern search. 相似文献
2.
评述了CAPP和PPC集成原理,在统一资源库的约束条件下,提出了基于GA-SA混合优化策略的CAPP和PPC的集成方法;建立了基于GA-SA算法的算法基本框架、算法模型;通过实例仿真表明,GA-SA混合寻优算法较单一的GA算法具有更好的应用效果。 相似文献
3.
针对基本遗传算法在优化设计中遇到的局部搜索能力不强、早熟收敛等问题,提出一种将模拟退火、Powell搜索方法与遗传算法相结合的混合遗传算法.在此基础上对普通圆柱蜗杆传动模糊优化设计进行了研究;数值计算表明,该混合退火遗传算法可以有效地克服基本遗传算法的上述缺陷,可以加速算法的收敛,具有良好的优化性能.并用该算法较好地解决了普通圆柱蜗杆传动的模糊优化设计. 相似文献
4.
A Modified Genetic Algorithm for Job Shop Scheduling 总被引:9,自引:0,他引:9
L. Wang D.-Z. Zheng 《The International Journal of Advanced Manufacturing Technology》2002,20(1):72-76
As a class of typical production scheduling problems, job shop scheduling is one of the strongly NP-complete combinatorial
optimisation problems, for which an enhanced genetic algorithm is proposed in this paper. An effective crossover operation
for operation-based representation is used to guarantee the feasibility of the solutions, which are decoded into active schedules
during the search process. The classical mutation operator is replaced by the metropolis sample process of simulated annealing
with a probabilistic jumping property, to enhance the neighbourhood search and to avoid premature convergence with controllable
deteriorating probability, as well as avoiding the difficulty of choosing the mutation rate. Multiple state generators are
applied in a hybrid way to enhance the exploring potential and to enrich the diversity of neighbour-hoods. Simulation results
demonstrate the effectiveness of the proposed algorithm, whose optimisation performance is markedly superior to that of a
simple genetic algorithm and simulated annealing and is comparable to the best result reported in the literature. 相似文献
5.
A simulated annealing/local search to minimize the makespan and total tardiness on a hybrid flowshop
S. M. Mousavi M. Zandieh M. Yazdani 《The International Journal of Advanced Manufacturing Technology》2013,64(1-4):369-388
Scheduling is a major issue faced every day in manufacturing systems as well as in the service industry, so it is essential to develop effective and efficient advanced manufacturing and scheduling technologies and approaches. Also, it can be said that bi-criteria scheduling problems are classified in two general categories respecting the approach used to solve the problem. In one category, the aim is to determine a schedule that minimizes a convex combination of two objectives and in the other category is to find a good approximation of the set of efficient solutions. The aim of this paper is to determine a schedule for hybrid flowshop problem that minimizes a convex combination of the makespan and total tardiness. For the optimization problem, a meta-heuristic procedure is proposed based on the simulated annealing/local search (SA/LS) along with some basic improvement procedures. The performance of the proposed algorithm, SA/LS, is compared with a genetic algorithm which had been presented in the literature for hybrid flowshop with the objective of minimizing a convex combination of the makespan and the number of tardy jobs. Several computational tests are used to evaluate the effectiveness and efficiency of the proposed algorithm against the other algorithm provided in the literature. From the results obtained, it can be seen that the proposed algorithm in comparison with the other algorithm is more effective and efficient. 相似文献
6.
为了实现齿轮箱典型故障的自适应准确辨识,提出一种遗传退火算法优化多核支持向量机的齿轮箱故障诊断模型。首先,将齿轮箱故障振动信号经验模式分解为多个内禀模态分量并提取其幅值能量特征;然后,再基于高斯核和多项式核构建多核支持向量机;最后,将表征齿轮箱故障特征的内禀模态分量能量输入到遗传退火算法优化的多核支持向量机进行故障模式辨识。理论分析表明,多核支持向量机能够逼近任意多元连续函数,遗传退火参数优化可快速准确得到多核支持向量机的全局最优参数向量。通过齿轮箱的故障模拟实验验证了该方法的有效性,结果表明,相比于传统的故障诊断模型,该方法显著提高了齿轮箱典型故障的诊断精度和泛化推广能力。 相似文献
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8.
Ali R. Yildiz 《The International Journal of Advanced Manufacturing Technology》2013,66(9-12):1319-1326
This paper presents a novel hybrid optimization approach based on teaching–learning based optimization (TLBO) algorithm and Taguchi’s method. The purpose of the present research is to develop a new optimization approach to solve optimization problems in the manufacturing area. This research is the first application of the TLBO to the optimization of turning operations in the literature The proposed hybrid approach is applied to two case studies for multi-pass turning operations to show its effectiveness in machining operations. The results obtained by the proposed approach for the case studies are compared with those of particle swarm optimization algorithm, hybrid genetic algorithm, scatter search algorithm, genetic algorithm and integration of simulated annealing, and Hooke–Jeeves patter search. 相似文献
9.
Khabat Abdi Mohammad Fathian Ehram Safari 《The International Journal of Advanced Manufacturing Technology》2012,60(5-8):723-732
A hybrid clustering method is proposed in this paper based on artificial immune system and simulated annealing. An integration of simulated annealing and immunity-based algorithm, combining the merits of both these approaches, is used for developing an efficient clustering method. Tuning the parameters of method is investigated using Taguchi method in order to select the optimum levels of parameters. Proposed method is implemented and tested on three real datasets. In addition, its performance is compared with other well-known meta-heuristics methods, such as ant colony optimization, genetic algorithm, simulated annealing, Tabu search, honey-bee mating optimization, and artificial immune system. Computational simulations show very encouraging results in terms of the quality of solution found, the average number of function evaluations and the processing time required, comparing with mentioned methods. 相似文献
10.
A population-based hybrid ant system for quadratic assignment formulations in facility layout design
A. S. Ramkumar S. G. Ponnambalam N. Jawahar 《The International Journal of Advanced Manufacturing Technology》2009,44(5-6):548-558
The facility layout design problem is an extensively studied research problem and belongs to nonpolynomial hard (NP-hard) combinatorial optimization problem. Quadratic assignment problem (QAP) is one of the formulations that is investigated for facility layout design because of its wide applicability. Ant colony optimization (ACO), a biologically inspired heuristic has centered on solving the QAP by achieving approximation as good as possible. This paper presents a population-based hybrid ant system (PHAS), which is an extension of the hybrid ant system (HAS) in which the size of the ant colony has been fixed. The performance of the proposed ant algorithm for QAP is compared with the existing metaheuristic implementations such as tabu search, reactive tabu search, simulated annealing, genetic hybrid method, HAS, and max–min ant system. The experimental results show that the proposed PHAS perform significantly better than the other existing algorithms of QAP. 相似文献
11.
Optimization of continuous-time production planning using hybrid genetic algorithms-simulated annealing 总被引:2,自引:0,他引:2
K. Ganesh M. Punniyamoorthy 《The International Journal of Advanced Manufacturing Technology》2005,26(1-2):148-154
Evolutionary algorithms are stochastic search methods that mimic the principles of natural biological evolution to produce better and better approximations to a solution and have been used widely for optimization problems. A general problem of continuous-time aggregate production planning for a given total number of changes in production rate over the total planning horizon is considered. It is very important to identify and solve the problem of continuous-time production planning horizon with varying production rates over the interval of the planning period horizon. Some of the researchers have proposed global search methods for the continuous-time aggregate production-planning problem. So far, less work is reported to solve the problem of continuous-time production planning using local search methods like genetic algorithms (GA) and simulated annealing (SA). So in this work, we propose a modified single objective evolutionary program approach, namely GA, SA, and hybrid genetic algorithms-simulated annealing (GA-SA) for continuous-time production plan problems. The results are compared with each other and it was found that the hybrid algorithm performs better. 相似文献
12.
针对制造和服务系统中纵向运输形式在双层过道布置问题中研究不足的情况,以实际布局方式为背景,对双层过道布置问题进行拓展,构建基于多纵向传输通道的双层过道布置问题混合整数规划模型,并提出一种混合模拟退火算法.该算法采用整数编码方式,以模拟退火算法为框架,结合2-Opt路径重连策略与逆转扰动操作,以避免陷入局部最优,同时采用... 相似文献
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14.
作业车间调度是一类求解较困难的组合优化问题,在考虑遗传算法早熟收敛问题结合模拟退火算法局部最优时能概率性跳出的特性,该特性最终使算法能够趋于全局最优。在此基础上,将遗传算法和模拟退火算法相结合,提出了一种基于遗传和模拟退火的混合算法,该算法将模拟退火算法赋予搜索过程一种时变性融入其中,具有明显的概率跳跃性。同时。通过选取Brandimarte基准问题和经典的Benchmarks基准问题进行分析,并应用实例对该算法进行了仿真研究。该结果表明,通过模拟退火算法与遗产算法相集合,可以使计算的收敛精度明显提高,是行之有效的,与传统的算法相比较,有较明显的优越性。 相似文献
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Wei Wei Wenhui Fan Zhongkai Li 《The International Journal of Advanced Manufacturing Technology》2014,75(9-12):1527-1536
Product configuration is one of the key technologies for mass customization. Traditional product configuration optimization targets are mostly single. In this paper, an approach based on multi-objective genetic optimization algorithm and fuzzy-based select mechanism is proposed to solve the multi-objective configuration optimization problem. Firstly, the multi-objective optimization mathematical model of product configuration is constructed, the objective functions are performance, cost, and time. Then, a method based on improved non-dominated sorting genetic algorithm (NSGA-II) is proposed to solve the configuration design optimization problem. As a result, the Pareto-optimal set is acquired by NSGA-II. Due to the imprecise nature of human decision, a fuzzy-based configuration scheme evaluation and select mechanism is proposed consequently, which helps extract the best compromise solution from the Pareto-optimal set. The proposed multi-objective genetic algorithm is compared with two other established multi-objective optimization algorithms, and the results reveal that the proposed genetic algorithm outperforms the others in terms of product configuration optimization problem. At last, an example of air compressor multi-objective configuration optimization is used to demonstrate the feasibility and validity of the proposed method. 相似文献
17.
为提高图像拼接的成功率,提出了一种基于自适应模拟退火和多分辨率搜索策略的图像自动拼接新方法。该新算法先自适应地选取配准区域,再以互信息为相似度评价标准,结合自适应模拟退火和多分辨率搜索策略的思想分别进行图像平移和旋转参数的全局优化和局部搜索,最后实现图像的拼接。通过对含噪声数字图像和医学超声图像进行的24次模拟拼接实验表明,该新算法较传统的多分辨率直接搜索法有精度高、速度快和抗噪声能力强的优点。由于结合了模拟退火算法的高精度和多分辨率搜索法的高效率,改进后的图像拼接算法将拼接成功率提高了12.5%,并将运算时间控制在可接受的范围内。 相似文献
18.
为了解决一类具有交货期瓶颈的作业车间调度问题,给出了基于订单优势的交货期满意度和交货期瓶颈资源确定方法,以工件拖期加权和最小为优化目标,建立了基于交货期满意度和瓶颈资源约束的作业车间调度模型;为了求解该调度模型,设计了一种基于模拟退火的混合粒子群算法,该算法采用随机工序表达方式进行编码,并在模拟退火算法中引入变温度参数来提高算法效率。通过随机仿真,分别采用PSO-SA、SA和PSO对所建立的调度模型进行求解,结果显示PSO-SA算法的广泛性好、求解效率高且算法的稳定性好,验证了模型和算法的有效性。 相似文献
19.
M. Rabiee Reza Sadeghi Rad M. Mazinani R. Shafaei 《The International Journal of Advanced Manufacturing Technology》2014,71(5-8):1229-1245
This paper addresses the problem of no-wait two-stage flexible flow shop scheduling problem (NWTSFFSSP) considering unrelated parallel machines, sequence-dependent setup times, probable reworks and different ready times to actualize the problem. The performance measure used in this study is minimizing maximum completion time (makespan). Because of the complexity of addressed problem, we propose a novel intelligent hybrid algorithm [called hybrid algorithm (HA)] based on imperialist competitive algorithm (ICA) which are combined with simulated annealing (SA), variable neighborhood search (VNS) and genetic algorithm (GA) for solving the mentioned problem. The hybridization is carried out to overcome some existing drawbacks of each of these three algorithms and also for increasing the capability of ICA. To achieve reliable results, Taguchi approach is used to define robust parameters' values for our proposed algorithm. A simulation model is developed to study the performance of our proposed algorithm against ICA, SA, VNS, GA and ant colony optimization (ACO). The results of the study reveal the relative superiority of HA studied. In addition, potential areas for further researches are highlighted. 相似文献
20.
P. Asokan G. Prabhakaran G. Satheesh Kumar 《The International Journal of Advanced Manufacturing Technology》2001,18(2):140-147
In this paper, the machine-cell grouping problem is considered with the objective of minimising the total moves and minimising
the cell load variation. We first review the literature on machine-cell grouping involving meta-heuristics. Then we integrate
the most powerful non-traditional algorithms, genetic algorithm (GA) and simulated annealing (SA) with the most robust computer
programming language "C", for cell grouping. The computational results obtained by applying the genetic algorithm and simulated
annealing are compared for their efficiency in solving the machine-cell grouping problems. 相似文献