着色Petri网模型检测工具的扩展及其在Web服务组合中的应用

Web服务组合的形式化描述和验证是一个重要的研究问题.为了更好地完成验证工作,提出了扩展着色Petri网的模型检测方法.首先,在着色Petri网原有的基于CTL的局部模型检测算法基础上,给出了获取模型检测证据/反例的算法,并在着色Petri网模型检测工具--CPN Tools--中使用ML(meta language)语言实现了这些算法,然后将扩展后的CPN模型检测工具应用在Web服务组合的验证问题中.该方法不仅可以验证Web服务组合是否存在逻辑错误,还能告诉用户发生错误的原因,为Web服务组合的验证提供了技术上的保障.实验表明对着色Petri网的模型检测工具的扩展是正确、有效的.     

Hybrid Metaheuristics Web Service Composition Model for QoS Aware Services

Recent advancements in cloud computing (CC) technologies signified that several distinct web services are presently developed and exist at the cloud data centre. Currently, web service composition gains maximum attention among researchers due to its significance in real-time applications. Quality of Service (QoS) aware service composition concerned regarding the election of candidate services with the maximization of the whole QoS. But these models have failed to handle the uncertainties of QoS. The resulting QoS of composite service identified by the clients become unstable and subject to risks of failing composition by end-users. On the other hand, trip planning is an essential technique in supporting digital map services. It aims to determine a set of location based services (LBS) which cover all client intended activities quantified in the query. But the available web service composition solutions do not consider the complicated spatio-temporal features. For resolving this issue, this study develops a new hybridization of the firefly optimization algorithm with fuzzy logic based web service composition model (F3L-WSCM) in a cloud environment for location awareness. The presented F3L-WSCM model involves a discovery module which enables the client to provide a query related to trip planning such as flight booking, hotels, car rentals, etc. At the next stage, the firefly algorithm is applied to generate composition plans to minimize the number of composition plans. Followed by, the fuzzy subtractive clustering (FSC) will select the best composition plan from the available composite plans. Besides, the presented F3L-WSCM model involves four input QoS parameters namely service cost, service availability, service response time, and user rating. An extensive experimental analysis takes place on CloudSim tool and exhibit the superior performance of the presented F3L-WSCM model in terms of accuracy, execution time, and efficiency.     

Optimization of a proton exchange membrane fuel cell membrane electrode assembly

A computational framework for fuel cell analysis and optimization is presented as an innovative alternative to the time consuming trial-and-error process currently used for fuel cell design. The framework is based on a two-dimensional through-the-channel isothermal, isobaric and single phase membrane electrode assembly (MEA) model. The model input parameters are the manufacturing parameters used to build the MEA: platinum loading, platinum to carbon ratio, electrolyte content and gas diffusion layer porosity. The governing equations of the fuel cell model are solved using Netwon’s algorithm and an adaptive finite element method in order to achieve near quadratic convergence and a mesh independent solution respectively. The analysis module is used to solve the optimization problem of finding the optimal MEA composition for maximizing performance. To solve the optimization problem a gradient-based optimization algorithm is used in conjunction with analytical sensitivities. By using a gradient-based method and analytical sensitivities, the framework presented is capable of solving a complete MEA optimization problem with state-of-the-art electrode models in approximately 30 min, making it a viable alternative for solving large-scale fuel cell problems.     

基于混合蚁群算法的异质车队低碳VRP研究

针对货运车辆在配送调度过程中产生大量碳排放的问题，建立模型将多种影响碳排放量的因素协同优化。模型中考虑了不同载重量的异质车队，两个节点之间有多条道路的柔性路径，以及车辆重量随卸货而减少的动态负载等因素，以碳排放量、行驶时间和行驶路程为优化目标，并加入了节点需求时间窗、根据速度变化划分路段、交接和卸货时间的约束。提出了一种混合蚁群算法，利用蚁群算法信息素强度更新方式保持群体记忆性，利用粒子群算法的快速收敛特性增加计算效率。通过随机数值算例的仿真优化与对比分析，验证了算法和模型的有效性。     

A revised ant algorithm for solving location–allocation problem with risky demand in a multi-echelon supply chain network

This study addresses a capacitated facility location and task allocation problem of a multi-echelon supply chain against risky demands. Two and three-echelon networks are considered to maximize profit. The study represents the problem by a bi-level stochastic programming model. The revised ant algorithm proposed in the study improves the existing ant algorithm by using new design of heuristic desirability and efficient greedy heuristics to solve the problem. A set of computational experiments is reported to not only allow to fine-tune the parameters of the algorithm but also to evaluate its performance for solving the problem proposed. Experiments reveal that the proposed solution algorithm can reach 95–99% of the optimal solution against risky demands while consuming only 1000th of the computational time for large-sized problems as compared to an optimization-based tool.     

Invertible Paradoxic Loop Structures for Transformable Design

We present an interactive tool compatible with existing software (Rhino/Grasshopper) to design ring structures with a paradoxic mobility, which are self-collision-free over the complete motion cycle. Our computational approach allows non-expert users to create these invertible paradoxic loops with six rotational joints by providing several interactions that facilitate design exploration. In a first step, a rational cubic motion is shaped either by means of a four pose interpolation procedure or a motion evolution algorithm. By using the representation of spatial displacements in terms of dual-quaternions, the associated motion polynomial of the resulting motion can be factored in several ways, each corresponding to a composition of three rotations. By combining two suitable factorizations, an arrangement of six rotary axes is achieved, which possesses a 1-parametric mobility. In the next step, these axes are connected by links in a way that the resulting linkage is collision-free over the complete motion cycle. Based on an algorithmic solution for this problem, collision-free design spaces of the individual links are generated in a post-processing step. The functionality of the developed design tool is demonstrated in the context of an architectural and artistic application studied in a master-level studio course. Two results of the performed design experiments were fabricated by the use of computer-controlled machines to achieve the necessary accuracy ensuring the mobility of the models.     

Efficient estimation of hybrid systems with applications to tracking

Particle filtering has been recognised as a superior alternative to the traditional estimation methods as it is applicable to nonlinear/non-Gaussian system. A central issue in real-time applications of particle filtering is its high computational cost. This problem is compounded when it is used in hybrid system estimation. A new particle filtering method for nonlinear/non-Gaussian hybrid system estimation is proposed in this article. The new method integrates the high-accuracy interacting multiple model particle filtering algorithm with the computationally efficient observation and transition-based most likely modes tracking particle filtering algorithm to get high-accuracy estimation with reduced computational load. The algorithm is applied to a manoeuvring target tracking application to demonstrate its efficiency.     

An ant algorithm for optimization of hole-making operations

This paper deals with the optimization of hole-making operations in conditions where a hole may need several tools to get completed. The objective of interest in the considered problem is to minimize the summation of tool airtime and tool switch time. This objective is affected by the sequence through which each operation of each hole is done. The problem is formulated as a 0–1 non-linear mathematical model. An ant algorithm is developed to solve the proposed mathematical model. The paper includes an illustrative example which shows the application of the proposed algorithm to optimizing the sequence of hole-making operations in a typical industrial part. The performance of the proposed algorithm is tested through solving six benchmark problems. The computational experience conducted in this research indicates that the proposed method is both effective and efficient.     

运输方式选择多目标优化问题的混合遗传算法

多式联运运输方式选择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运输方式选择多目标优化问题的数学模型及虚拟运输网络图;其次,将基于信息熵的多属性决策方法引入适应度函数的设计中,提出了一种求解多式联运运输方式选择多目标优化问题的混合遗传算法,给出了染色体编码、遗传算子设计、染色体有效性判断和修正的方法;最后用示例对算法的有效性进行了验证。     

Construction of a parallel computational model by composition of computational facilities

We consider a general algorithm for constructing a parallel numerical model by composition of several computational objects. The only requirement for the applicability of the proposed algorithm is for the disturbance propagation speed to be finite. We present one possible approach to map a numerical model onto an object-oriented program model. Some results of numerical experiments on solving the heat conduction equation in linear and nonlinear cases are discussed.     

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。     

New Model and Algorithm for Hardware/Software Partitioning

This paper focuses on the algorithmic aspects for the hardware/software （HW/SW） partitioning which searches a reasonable composition of hardware and software components which not only satisfies the constraint of hardware area but also optimizes the execution time. The computational model is extended so that all possible types of communications can be taken into account for the HW/SW partitioning. Also, a new dynamic programming algorithm is proposed on the basis of the computational model, in which source data, rather than speedup in previous work, of basic scheduling blocks are directly utilized to calculate the optimal solution. The proposed algorithm runs in O（n·A） for n code fragments and the available hardware area A. Simulation results show that the proposed algorithm solves the HW/SW partitioning without increase in running time, compared with the algorithm cited in the literature.     

基于混合差分遗传算法的Bouc-Wen迟滞模型辨识策略

提出一种应用于Bouc-Wen迟滞模型的混合差分遗传算法.该算法可以自适应调节缩放因子来改变交叉概率因子的值,同样也可以自动调节交叉概率因子来调整缩放因子的值.通过缩放因子和交叉概率因子的混合作用,能使算法前期维持种群多样性,同时强化对全局最优值的搜索能力,从而快速寻找最适模型参数.在算法后期,随着局部最优值搜索能力的...     

A multi-mode resource-constrained scheduling problem in the context of port operations

We discuss a problem of attending ships within agreed time limits at a port under the condition of the first come first served order. In addition, we indicate the use of the developed tool to support decisions at a strategic level with the objective of improving the attendance of the ships. The tool is based on a mathematical model of a multi-mode resource-constrained scheduling problem and on an extension of a differential evolution algorithm. We illustrate the implementation by computational tests with data generated on the basis of the characteristics of a real port environment.     

Dynamic speed control of a machine tool with stochastic tool life: analysis and simulation

We discuss a tool management model for a flexible machine equipped with a tool magazine, variable cutting speed, and sensors to monitor tool wear, when tool life due to flank wear is stochastic. The objective is to adjust the cutting speed as a function of remaining distance, each time a tool change occurs, in order to minimize the expected processing time (sum of cutting and tool setup time). We address the computational aspects of finding optimal decision rules and we present numerical results suggesting that easily computed decision rules of a simple static model are near-optimal for our dynamic programming model. Dynamic adjustment is assessed with simulation experiments.     

Searching oligo sets of human chromosome 12 using evolutionary strategies

DNA Microarray is a powerful tool to measure the level of a mixed population of nucleic acids at one time, which has great impact in many aspects of life sciences research. In order to distinguish nucleic acids with very similar composition by hybridization, it is necessary to design microarray probes with high specificities and sensitivities. Highly specific probes correspond to probes having unique DNA sequences; whereas highly sensitive probes correspond to those with melting temperature within a desired range and having no secondary structure. The selection of these probes from a set of functional DNA sequences (exons) constitutes a computationally expensive discrete non-linear search problem. We delegate the search task to a simple yet effective Evolution Strategy algorithm. The computational efficiency is also greatly improved by making use of an available bioinformatics tool.     

A feasible flow-based iterative algorithm for the two-level hierarchical time minimization transportation problem

The THTMTP (two-level hierarchical time minimization transportation problem) is an important problem arising in industries. In literature, there are only two approaches with shortcomings to solve the problem. In this paper, the THTMTP is formulated as a mathematical model applicable to the case in which the total available supply at the sources is no less than the total demand at the destinations. A feasible flow-based iterative algorithm named THTMTP-A is proposed to solve the THTMTP by constructing network with lower and upper arc capacities. It is proved that the THTMTP-A algorithm can find the optimal solution to the THTMTP in a polynomial time. The proposed THTMTP-A algorithm has good performance in terms of computer implementation, computational time and required memory for computation, and hence overcomes successfully the shortcomings of the two existing approaches. Computational experiments validate that the THTMTP-A algorithm is an efficient and robust method to solve the THTMTP, and can serve as efficient tool to solve other related optimization problems.     

基于混合滤波的四轴飞行器的姿态解算

针对四轴飞行器的姿态解算出现的姿态角数据漂移问题,提出一种基于Mahony滤波和互补滤波相结合的混合滤波算法,将传感器采集到的加速度、角速度以及磁场强度数据进行融合,利用加速度计和磁力计的向量偏差来对姿态解算过程中陀螺仪产生的积分累计误差进行修正.最后,建立姿态解算测试平台对混合滤波算法进行实验验证.实验结果表明,采用混合滤波算法的一次迭代滤波所需的平均用时为3.826 ms,比其他算法的平均用时短,混合滤波能有效地修正陀螺仪的积分累计误差,在降低运算复杂度的同时提高姿态解算的精度.     

Performance-optimized applied identification of separabledistributed-parameter processes

Studies practical algorithms for parametric identification of cross-directional processes from input/output data. Instead of working directly with the original two-dimensional array of the high-resolution profile scans, the proposed algorithms use separation properties of the problem. It is demonstrated that by estimating and identifying in turn cross directional and time responses of the process, it is possible to obtain unbiased least-square error estimates of the model parameters. At each step, a single data sequence is used for identification which ensures high computational performance of the proposed algorithm. A theoretical proof of algorithm convergence is presented. The discussed algorithms are implemented in an industrial identification tool and the note includes a real-life example using paper machine data     

Adaptation and learning in control of voluntary movement by the central nervous system

In order to control voluntary movements, the central nervous system must solve the following three computational problems at different levels: (1) the determination of a desired trajectory in visual coordinates; (2) the transformation of its coordinates into body coordinates; and (3) the generation of motor command. Concerning these problems, relevant experimental observations obtained in the field of neuroscience are briefly reviewed. On the basis of physiological information and previous models, we propose computational theories and a neural network model which account for these three problems. (1) A minimum torque-change model which predicts a wide range of trajectories in human multi-joint arm movements is proposed as a computational model for trajectory formation. (2) An iterative learning scheme is presented as an algorithm which solves the coordinate transformation and the control problem simultaneously. This algorithm can be regarded as a Newton-like method in function spaces. (3) A neural network model for generation of motor command is proposed. This model contains internal neural models of the motor system and its inverse system. The inverse-dynamics model is acquired by heterosynaptic plasticity using a feedback motor command (torque) as an error signal. The hierarchical arrangement of these neural networks and their global control are discussed. Their applications to robotics are also discussed.