共查询到20条相似文献，搜索用时 15 毫秒
1.
We consider the problem of placing copies of objects in a distributed web server system to minimize the cost of serving read and write requests when the web servers have limited storage capacities. We formulate the problem as a 0–1 optimization problem and present a hybrid particle swarm optimization algorithm to solve it. The proposed hybrid algorithm makes use of the strong global search ability of particle swarm optimization (PSO) and the strong local search ability of tabu search to obtain high quality solutions. The effectiveness of the proposed algorithm is demonstrated by comparing it with the genetic algorithm (GA), simple PSO, tabu search, and random placement algorithm on a variety of test cases. The simulation results indicate that the proposed hybrid approach outperforms the GA, simple PSO, and tabu search. 相似文献
2.
In this paper a population based evolutionary optimization methodology called Opposition based Harmony Search Algorithm (OHS) is applied for the optimization of system coefficients of adaptive infinite impulse response (IIR) system identification problem. The original Harmony Search (HS) algorithm is chosen as the parent one and opposition based approach is applied to it with an intention to exhibit accelerated near global convergence profile. During the initialization, for choosing the randomly generated population/solution opposite solutions are also considered and the fitter one is selected as apriori guess for having faster convergence profile. Each solution in Harmony Memory (HM) is generated on the basis of memory consideration rule, a pitch adjustment rule and a re-initialization process which gives the optimum result corresponding to the least error fitness in multidimensional search space. Incorporation of different control parameters in basic HS algorithm results in balancing of exploration and exploitation of search space. The proposed OHS based system identification approach has alleviated from inherent drawbacks of premature convergence and stagnation, unlike Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE). The simulation results obtained for some well known benchmark examples justify the efficacy of the proposed OHS based system identification approach over GA, PSO and DE in terms of convergence speed, identifying the system plant coefficients and mean square error (MSE) fitness values produced for both same order and reduced order models of adaptive IIR filters. 相似文献
3.
Sidhartha Panda 《Journal of The Franklin Institute》2011,348(8):1903-1926
Power-system stability improvement by a static synchronous series compensator (SSSC)-based damping controller is thoroughly investigated in this paper. Both local and remote signals with associated time delays are considered in the present study. The design problem of the proposed controller is formulated as an optimization problem, and differential evolution (DE) algorithm is employed to search for the optimal controller parameters. The performances of the proposed controllers are evaluated under different disturbances for both single-machine infinite-bus power system and multi-machine power system. The performance of the proposed controllers with variations in the signal transmission delays has also been investigated. Simulation results are presented and compared with a recently published modern heuristic optimization technique under various disturbances to show the effectiveness and robustness of the proposed approach. The performances of the proposed controllers are also evaluated under N−2 contingency situation. 相似文献
4.
Delay-dependent stability for uncertain cellular neural networks with discrete and distribute time-varying delays 总被引：1，自引：0，他引：1
In this paper, the problem of stability of uncertain cellular neural networks with discrete and distribute time-varying delays is considered. Based on the Lyapunov function method and convex optimization approach, a new delay-dependent stability criterion of the system is derived in terms of LMI (linear matrix inequality). In order to solve effectively the LMI as a convex optimization problem, the interior-point algorithm is utilized in this work. A numerical example is given to show the effectiveness of our results. 相似文献
5.
《Journal of The Franklin Institute》2023,360(3):1835-1869
The optimal control strategy constructed in the form of a state feedback is effective for small state perturbations caused by changes in modeling uncertainty. In this paper, we investigate a robust suboptimal feedback control (RSPFC) problem governed by a nonlinear time-delayed switched system with uncertain time delay arising in a 1,3-propanediol (1,3-PD) microbial fed-batch process. The feedback control strategy is designed based on the radial basis function to balance the two (possibly competing) objectives: (i) the system performance (concentration of 1,3-PD at the terminal time of the fermentation) is to be optimal; and (ii) the system sensitivity (the system performance with respect to the uncertainty of the time-delay) is to be minimized. The RSPFC problem is subject to the continuous state inequality constraints. An exact penalty method and a novel time scaling transformation approach are used to transform the RSPFC problem into the one subject only to box constraints. The resulting problem is solved by a hybrid optimization algorithm based on a filled function method and a gradient-based algorithm. Numerical results are given to verify the effectiveness of the developed hybrid optimization algorithm. 相似文献
6.
针对数据库多连接查询优化问题,提出一种基于遗传禁忌算法的数据库多连接查询优化策略。把遗传算法作为查询优化的主框架,禁忌搜索作为遗传算法的变异算子,增加种群多样性,克服遗传算法收敛慢、局部搜索能力差等缺陷。仿真结果表明,遗传禁忌算法加快了求解数据库多连接查询优化问题的速度,而且提高了查询优化效率,得到较满意的查询优化结果。 相似文献
7.
TSP问题是一类典型的NP完全问题,禁忌搜索算法是解决此类问题的智能优化方法之一。文章在研究了禁忌搜索算法的基本原理和算法步骤的基础上,建立了求解TSP问题的数学模型,设计了一个求解TSP问题的禁忌搜索算法程序,并进行了实验测试,实验结果表明,禁忌搜索算法能够有效地解决TSP问题。 相似文献
8.
Wongphaka Wongrat Ali Elkamel Peter L. Douglas Ali Lohi 《Journal of The Franklin Institute》2011,348(7):1318-1338
Rice drying synthesis is an essential operation that has to be done carefully and cost-effectively. Rice is harvested at high moisture content and hence must be dried within 24 h for safe storage. However, improper drying can cause fissuring in the rice grain, and thus greatly reduce its market value. Multi-pass drying systems are therefore used to gradually bring moisture content to desired level.The problem of rice synthesis, considered in this study, seeks the configuration of units and their corresponding operating conditions that maximize rice quality. This problem is formulated as a mixed-integer dynamic optimization problem. The integer part of the problem reflects process alternatives while the dynamic part originates from nonlinear differential-algebraic equations describing the drying behavior of a rice grain.Clearly such a formidable problem is not easy to solve. Hence, we propose an approach that makes use of two algorithms: a genetic algorithm to search for the best configuration of units and a control vector parameterization approach that optimizes the operating conditions for each configuration. We demonstrate the effectiveness of the approach on a case study. 相似文献
9.
This paper presents the design and performance analysis of Proportional Integral Derivate (PID) controller for an Automatic Voltage Regulator (AVR) system using recently proposed simplified Particle Swarm Optimization (PSO) also called Many Optimizing Liaisons (MOL) algorithm. MOL simplifies the original PSO by randomly choosing the particle to update, instead of iterating over the entire swarm thus eliminating the particles best known position and making it easier to tune the behavioral parameters. The design problem of the proposed PID controller is formulated as an optimization problem and MOL algorithm is employed to search for the optimal controller parameters. For the performance analysis, different analysis methods such as transient response analysis, root locus analysis and bode analysis are performed. The superiority of the proposed approach is shown by comparing the results with some recently published modern heuristic optimization algorithms such as Artificial Bee Colony (ABC) algorithm, Particle Swarm Optimization (PSO) algorithm and Differential Evolution (DE) algorithm. Further, robustness analysis of the AVR system tuned by MOL algorithm is performed by varying the time constants of amplifier, exciter, generator and sensor in the range of ?50% to +50% in steps of 25%. The analysis results reveal that the proposed MOL based PID controller for the AVR system performs better than the other similar recently reported population based optimization algorithms. 相似文献
10.
细菌觅食算法在求解水库优化调度问题时,以固定的步长进行趋向操作,同时以固定概率对细菌个体进行随机驱散操作,虽然可以一定程度上增加种群多样性,但是在进化后期容易使优秀的个体流失,影响算法的寻优质量。针对该问题,文章提出步长自适应调整和驱散概率自适应调整两项改进策略,根据算法进化程度和细菌个体的能量值动态调整趋向操作的步长和驱散操作的概率,使算法进化过程中尽量保证种群多样性的基础上,提高细菌个体的觅食能力,进一步促进算法达到局部搜索和全局优化之间的平衡。将改进的细菌觅食算法应用于乌江梯级水库群的联合优化调度问题,模拟结果表明:改进细菌觅食算法具有较强的全局寻优能力,适合求解梯级水库联合优化调度问题。 相似文献
11.
《Journal of The Franklin Institute》2006,343(4-5):420-435
This paper describes the application of the genetic algorithm for the optimization of the control parameters in parallel hybrid electric vehicles (HEV). The HEV control strategy is the algorithm according to which energy is produced, used, and saved. Therefore, optimal management of the energy components is a key element for the success of a HEV. In this study, based on an electric assist control strategy (EACS), the fitness function is defined so as to minimize the vehicle engine fuel consumption (FC) and emissions. The driving performance requirements are then considered as constraints. In addition, in order to reduce the number of the decision variables, a new approach is used for the battery control parameters. Finally, the optimization process is performed over three different driving cycles including ECE-EUDC, FTP and TEH-CAR. The results from the computer simulation show the effectiveness of the approach and reduction in FC and emissions while ensuring that the vehicle performance is not sacrificed. 相似文献
12.
13.
The problem of designing optimal process-specific rules for non-parametric tuning is undertaken in the paper. It is shown that producing non-parametric process-specific optimal tuning rules for PID controllers leads to the problem that can be characterized as optimization under uncertainty. This happens due to the fact that tuning rules, unlike tuning constants, are produced not for a particular process or plant model but for a set of models from a certain domain. The novelty of the proposed approach is that the problem of obtaining optimal tuning rules for a flow process is formulated and solved as a problem of optimization of an integral performance criterion parametrized through values that define the domain of available process models. The considered non-parametric tuning assumes the use of the modified relay feedback test (MRFT) recently proposed in the literature. It allows one to tune the PID controller satisfying the requirements to gain or phase margins that is achieved through coordinated selection of tuning rules and test parameters. This approach constitutes a holistic approach to tuning. In the present paper, optimal tuning rules coupled with MRFT, for flow loops, are proposed. Final results are presented in the form of tables containing coefficients of optimal tuning rules for the PI controller, obtained for a number of specified gain margins. The produced non-parametric tuning rules well agree with the practice of loop tuning. 相似文献
14.
《Journal of The Franklin Institute》2022,359(2):859-869
In this paper, we considered a time-optimal control problem for a new type of linear parameter varying (LPV) system which is obtained through data identification in the process of dealing with actual problems. The addition of non-linear terms is compensation for the method that does not require linear expansion at the equilibrium point. Since the objective function is the terminal time which is an implicit function concerning decision variables, it is a non-standard optimal control problem with uncertain terminal time. To find the global optimal solution to this problem, firstly, the control parameterization method is used to transform it into a nonlinear optimization problem of parameter selection, and then the modifed particle swarm optimization (PSO) algorithm is combined to solve the equivalent nonlinear programming problem. Numerical examples are used to illustrate the effectiveness of the proposed algorithm. 相似文献
15.
《Journal of The Franklin Institute》2023,360(13):9579-9601
The current parking trajectory planning algorithms based on geometric connections or formulation of optimization problems in automatic parking systems have strict requirements on the starting position, lower planning efficiency and discontinuous curvature of the reference trajectory. In order to solve these problems, a hierarchical planning algorithm which is combined with nonlinear optimization and the improved RRT* algorithm (Rapidly-exploring Random Tree Star) with Reeds-Shepp curve is proposed in this paper. First, the improved RRT*RS algorithm with the rapid repulsion-straddle experiment is designed for enhancing the efficiency of path planning. Second, because of the shortcomings of the Reeds-Shepp curve that can meet the minimum turning radius but not realize the continuous curvature of the path, a nonlinear optimization problem based on convex-set obstacle constraints is formulated and solved. Finally, simulation results show that the proposed parking trajectory planning algorithm in this paper can plan an effective parking trajectory with continuous curvature in different starting positions and multiple parking scenarios. 相似文献
16.
为了实现变电站内无功电压优化控制,提出了采用禁忌搜索算法进行无功电压优化控制问题的求解。以最大限度地降低功率损耗、提高电压质量和减少变压器的调节次数及电容器组的投切次数为目标,建立了相应的数学模型,并考虑系统潮流、控制变量、状态变量、器件动作次数的约束条件。采用数值仿真的方法进行了验证,仿真结果表明提出的方法可以得到最优解,解的质量较高。 相似文献
17.
Amir-R. Khorsand 《Journal of The Franklin Institute》2007,344(5):595-612
Evolutionary structural design has been the topic of much recent research; however, such designs are usually hampered by the time-consuming stage of prototype evaluations using standard finite element analysis (FEA). Replacing the time-consuming FEA by neural network approximations may be a computationally efficient alternative, but the error in such approximation may misguide the optimization procedure. In this paper, a multi-objective meta-level (MOML) soft computing-based evolutionary scheme is proposed that aims to strike a balance between accuracy vs. computational efficiency and exploration vs. exploitation. The neural network (NN) is used here as a pre-filter when fitness is estimated to be of lesser significance while the standard FEA is used for solutions that may be optimal in their current population. Furthermore, a fuzzy controller updates parameters of the genetic algorithm (GA) in order to balance exploitation vs. exploration in the search process, and the multi-objective GA optimizes parameters of the membership functions in the fuzzy controller. The algorithm is first optimized on two benchmark problems, i.e. a 2-D Truss frame and an airplane wing. General applicability of the resulting optimization algorithm is then tested on two other benchmark problems, i.e. a 3-layer composite beam and a piezoelectric bimorph beam. Performance of the proposed algorithm is compared with several other competing algorithms, i.e. a fuzzy-GA-NN, a GA-NN, as well as a simple GA that only uses only FEA, in terms of both computational efficiency and accuracy. Statistical analysis indicates the superiority as well as robustness of the above approach as compared with the other optimization algorithms. Specifically, the proposed approach finds better structural designs more consistently while being computationally more efficient. 相似文献
18.
《Information processing & management》2022,59(2):102854
As a recent swarm intelligence optimization algorithm, sparrow search algorithm (SSA) is widely adopted in many real-world problems. However, the solutions to the limitations of SSA (such as low accuracy of convergence and tendency of trapping into local optimum) are still not available. To address these issues, we propose an enhanced multi-strategies sparrow search algorithm (EMSSA) based on three strategies specifically addressing the limitations of SSA: 1) in the uniformity-diversification orientation strategy, we propose an adaptive-tent chaos theory to allow more diversity and greater randomness in the initial population; 2) in the hazard-aware transfer strategy, we construct a weighted sine and cosine algorithm based on the growth function to avoid trapping into the state of local optima stagnation; 3) in the dynamic evolutionary strategy, we design the similar perturbation function and introduce the triangle similarity theory to improve the exploration capability. The performance of EMSSA in solving the continuous optimization problems about the 23 benchmark functions, CEC2014, and CEC2017 problems is much improved than that of SSA and other state-of-the-art algorithms. Furthermore, the results of the density peak clustering optimization show that the EMSSA outperforms SSA. 相似文献
19.
Raid Al-Aomar 《Journal of The Franklin Institute》2011,348(7):1506-1522
This paper describes a simulation-based approach for developing a lean production system of multi-lean measures. Three lean measures are defined to characterize the leanness of the underlying production system: productivity, cycle time, and work-in-process inventory. An optimized setting to certain operational parameters is determined so that a best tradeoff of the three lean measures is reached. The problem formulation results in a multi-objective optimization problem with no closed-form definition of problem objective functions and constraints. The solution approach utilizes Discrete Event Simulation (DES) to deploy lean techniques and model lean measures under process variability and plant constraints and dynamics. A direct search method (i.e., Simulated Annealing (SA)) is used to search of problem domain. A model-based Value Mapping (VM) is used for combining the conflicting multi-lean measures and guiding the SA search for optima. The DES model is also used to develop a future state dynamic Value Stream Map (VSM) of the optimized production process. The approach is applied to an example production system where the capacity of material handling conveyors and the size of maintenance crew are optimized to develop a lean system in terms of three lean measures. Little’s formula is used to verify the simulation assessment of lean measures. Optimization results are also used to demonstrate the conflict among lean measures, the impact of process variability on lean measures, and the role of VM in reaching an efficient tradeoff of multi-lean measures. 相似文献
20.
研究了多机协同多目标攻击空战决策问题。它是依据空战形势，寻求M架友机对N架敌机的一个适当的攻击分配方案，以实现最优的期望攻击效果。为此，本文首先建立了决策问题的数学模型，接着应用混合自适应遗传算法对其进行求解。在混合自适应遗传算法中，将一种局部搜索方法引入自适应遗传算法以提高其搜索能力。同时，设计了用于满足决策问题的非常规交叉算子。仿真实验结果表明所设计的混合自适应遗传算法比自适应遗传算法能更有效的解决协同多目标攻击空战决策问题。 相似文献