Two hybrid differential evolution algorithms for engineering design optimization

This paper presents two hybrid differential evolution algorithms for optimizing engineering design problems. One hybrid algorithm enhances a basic differential evolution algorithm with a local search operator, i.e., random walk with direction exploitation, to strengthen the exploitation ability, while the other adding a second metaheuristic, i.e., harmony search, to cooperate with the differential evolution algorithm so as to produce the desirable synergetic effect. For comparison, the differential evolution algorithm that the two hybrids are based on is also implemented. All algorithms incorporate a generalized method to handle discrete variables and Deb's parameterless penalty method for handling constraints. Fourteen engineering design problems selected from different engineering fields are used for testing. The test results show that: (i) both hybrid algorithms overall outperform the differential evolution algorithms; (ii) among the two hybrid algorithms, the cooperative hybrid overall outperforms the other hybrid with local search; and (iii) the performance of proposed hybrid algorithms can be further improved with some effort of tuning the relevant parameters.     

基于混合总线的虚拟仪器教学实验系统设计

针对自动测试、虚拟仪器及总线设备类课程的试验设备不足,在VXI、GPIB及LXI混合总线的基础上构建了一个虚拟仪器教学实验系统,并以C#.NET结合虚拟仪器技术建立了整个系统的软件架构;介绍了该系统的硬件软件设计方法及其实现的关键技术;通过课程实践表明,该系统功能强且扩展性好,满足了实验的要求,节约了实验成本。     

电离层垂测仪系统信号源设计与实现

为了克服传统电离层垂测仪射频信号软件延时的缺点,提高大气电离层垂测仪系统信号源产生信号的精度,更充分地研究电离层物理特性,利用DDS技术和嵌入μC/OS-Ⅱ操作系统的miniARM微处理器,给出了一个新型的电离层垂测仪系统信号源的架构方案;该系统利用了32位ARM嵌入式微处理器LPC2220的定时器匹配硬件功能,控制DDS芯片Q2368完成无延时的相位调制;实验结果表明,该信号源所产生的高频信号具有精度高,频率转换时间短等特点,其他信号也完全满足电离层垂测仪对信号源的技术要求.     

An integrated fuzzy TOPSIS and MCGP approach to supplier selection in supply chain management

Supplier selection is an important issue in supply chain management. In recent years, determining the best supplier in the supply chain has become a key strategic consideration. However, these decisions usually involve several objectives or criteria, and it is often necessary to compromise among possibly conflicting factors. Thus, the multiple criteria decision making (MCDM) becomes a useful approach to solve this kind of problem. Considering both tangible and intangible criteria, this study proposes integrated fuzzy techniques for order preference by similarity to ideal solution (TOPSIS) and multi-choice goal programming (MCGP) approach to solve the supplier selection problem. The advantage of this method is that it allows decision makers to set multiple aspiration levels for supplier selection problems. The integrated model is illustrated by an example in a watch firm.     

Design of a performance-oriented workplace e-learning system using ontology

E-learning is emerging as a popular learning approach utilized by many organizations. Despite the ever increasing practices of e-learning in the workplace, most e-learning applications fail to meet learners’ needs or serve organization’s quests for success. Significant gaps exist between organizational interests and individual needs when they come to e-learning, which make e-learning applications less goal-effective. To solve this problem, a performance-oriented approach is presented in this study. Key performance indicators (KPIs) are set up to clarify organizational training needs, and help learners establish rational learning objectives. In addition, ontology is used for constructing formal and machine-understandable conceptualization of the performance-oriented learning environment. Using this approach, a KPI-oriented learning ontology and prototype system have been developed and evaluated to demonstrate the effectiveness of the approach.     

A novel thermo-pneumatic peristaltic micropump with low temperature elevation on working fluid

This work presents a novel thermo-pneumatic peristaltic micropump with low temperature elevation on working fluid. The proposed device, which consists of two separate zones for air-heating and fluid-squeezing, is realized by using micromachining techniques. Also, the device can be operated by using a small and simple actuation circuitry with low applied voltages. Under similar operational conditions, the proposed micropump shows similar fluid-pumping performance when compared with the conventional design of thermo-pneumatic micropumps. However, for the proposed design, the temperature elevation on the fluid-pumping area is as small as about 2.0 K, which is less than 8% of that generated by the conventional design. Furthermore, by applying higher voltages, larger flow rate can be achieved with relatively small increase in temperature elevation. Due to low temperature elevation on working fluid, the proposed device is suitable for the applications such as DNA chips or protein chips. In addition, because of its small size and simple actuation scheme, potentially the proposed device can be integrated into the devices for point-of-care applications.     

Impact of media richness and flow on e-learning technology acceptance

Advances in e-learning technologies parallels a general increase in sophistication by computer users. The use of just one theory or model, such as the technology acceptance model, is no longer sufficient to study the intended use of e-learning systems. Rather, a combination of theories must be integrated in order to fully capture the complexity of e-learners, who are both system users and learners. The current research presents an integrated theoretical framework to study users’ acceptance of streaming media for e-learning. Three streams of research provide the basis for this integrated framework: the technology acceptance model, flow theory and media richness theory. Students enrolled in an online section of an information systems course used one of three different combinations of text, streamed audio and streamed video. Regression analysis was used to test the hypotheses in this field experiment. Perceived ease of use was a predictor of perceived usefulness; both the perceived usefulness and the attitude of the user were predictors of intention to use. Richer content-presentation types were positively correlated with higher concentration levels but showed mixed results when correlated with perceived usefulness. Results from this study have practical implications for those interested in integrating streaming media into e-learning.     

Spare parts inventory control considering stochastic growth of an installed base

Installed base is a measure describing the number of units of a particular system actually in use. To maintain the performance of the installed units, spare parts inventory control is extremely important and becomes very challenging when the installed base changes over time. This problem is often encountered when a manufacturer starts to deliver a new product to customers and agrees to provide spare parts to replace failed units in the future. To cope with the resulting non-stationary stochastic maintenance demand, a spare parts control strategy needs to be carefully developed. The goal is to ensure that timely replacements can be provided to customers while minimizing the overall cost for spare parts inventory control. This paper provides a model for the aggregate maintenance demand generated by a product whose installed base grows according to a homogeneous Poisson process. Under a special case where the product’s failure time follows the exponential distribution, the closed form solutions for the mean and variance of the aggregate maintenance demand are obtained. Based on the model, a dynamic (Q, r) restocking policy is formulated and solved using a multi-resolution approach. Two numerical examples are provided to demonstrate the application of the proposed method in controlling spare parts inventory under a service level constraint. Simulation is utilized to explore the effectiveness of the multi-resolution approach.     

Heuristic algorithms for two-machine flowshop with availability constraints

The majority of the scheduling studies carry a common assumption that machines are available all the time. However, machines may not always be available in the scheduling period due to breakdown or preventive maintenance. Taking preventive maintenance activity into consideration, we dealt with the two-machine flowshop scheduling problem with makespan objective. The preventive maintenance policy in this paper was dependent on the number of finished jobs. The integer programming model was proposed. We combined two recent constructive heuristics, HI algorithm and H algorithm, with Johnson’s algorithm, and named the combined heuristic H&J algorithm. We also developed a constructive heuristic, HD, with time complexities O(n²). Based on the difference in job processing times on two machines, both H&J and HD showed good performance, and the latter was slightly better. The HD algorithm was able to obtain the optimality in 98.88% of cases. We also employed the branch and bound (B&B) algorithm to obtain the optimum. With a good upper bound and a modified lower bound, the proposed B&B algorithm performed significantly effectively.     

New delay-dependent exponential stability criteria of BAM neural networks with time delays

In this paper, the global exponential stability is investigated for the bi-directional associative memory networks with time delays. Several new sufficient conditions are presented to ensure global exponential stability of delayed bi-directional associative memory neural networks based on the Lyapunov functional method as well as linear matrix inequality technique. To the best of our knowledge, few reports about such “linearization” approach to exponential stability analysis for delayed neural network models have been presented in literature. The method, called parameterized first-order model transformation, is used to transform neural networks. The obtained conditions show to be less conservative and restrictive than that reported in the literature. Two numerical simulations are also given to illustrate the efficiency of our result.