Firefly algorithms (FA) appeared about five years ago, in 2008, and the literature has expanded dramatically with diverse applications. In this chapter, we introduce the standard firefly algorithm, then briefly review the variants, together with a selection of recent publications. We also analyze the characteristics of FA and try to answer the question of why FA is so efficient.
No abstract is provided for this article.
The shunt reactors are important components in the EHV/UHV (Eltra/Ultra High Voltage) power systems used for the voltage regulation issues. One of their important roles is to compensate the reactive power. Typically for such compensation the fixed shunt reactors are used. Alternative concepts introduced recently are the controllable reactors. The controlling effect of orthogonal flux type controllable reactor is achieved by controlling the saturation level of the parts of the magnetic core (saturable reactor). In this paper we present an efficient approach for the simulation of such controllable reactors using Integral Equation Method (IEM). The key information when analyzing this kind of devices are the controllable reluctances. The paper demonstrates usage of IEM for the computation of the inductances as a function of the reluctance changes depending on the saturation levels of the magnetic material. The results are compared with the calculation results obtained by an equivalent magnetic circuit calculation model.
No abstract is provided for this article.
No abstract is provided for this article.
Purpose This study aims to introduce and prove the existence of negative rivalry in use, which should be an integral part of goods taxonomy, from the perspective of knowledge sharing and further present the critical role of knowledge sharing in the digital economy era by reviewing the literature, theoretical analysis and real-world cases. It also aims to open a new door for re-recognizing knowledge sharing through an interdisciplinary framework. Design/methodology/approach This study proves the existence of negative rivalry through both theoretical analysis (4-E model) and real-world cases, especially the cases of Tesla and ChatGPT, and puts up new reasons for knowledge sharing in the era of digital economy through interdisciplinary methods. Findings The authors find out that there are many new phenomena beyond the spectrum of current goods taxonomy, especially beyond the priori understanding of rivalry in use. Digital platforms such as ChatGPT should have been “used up” in no time, for they have attracted so massive users according to (positive) rivalry in use, or should have been unchanged at most according to non-rivalry in use. But what we see is their rapid upgrading with the help of billions of users. The reason is that negative rivalry in use has completely been neglected. The authors find out that the process of knowledge sharing unveils the unrecognized attribute of rivalry in use, i.e. negative rivalry in use, which serves as the fundamental driving force of the breathtaking growth of all kinds of digital platforms. Originality/value This study originally put up a 4-E model of goods’ rivalry in use, the brand new term, i.e. negative rivalry in use, and proves its existence and working mechanism from the perspective of knowledge sharing. With the introduction of negative rivalry in use, the traditional four-type goods classification model is extended into a six-type model, which may be a sound marginal contribution, to the best of the authors’ knowledge. The study may reshape people’s mindsets on goods usage, especially knowledge management, into a more open-sharing model because it shows that there is very likely a positive-sum game instead of a zero- or negative-sum game for shared knowledge per se and its platform in the process of knowledge sharing in the era of digital economy.
SUMMARY A new metaheuristic optimization algorithm is developed to solve truss optimization problems. The new algorithm, called cuckoo search (CS), is examined by solving five truss design optimization problems with increasing numbers of design variables and complexity in constraints. The performance of the CS algorithm is further compared with various classical and advanced algorithms, selected from a wide range of the state‐of‐the‐art algorithms in the area. The results identify that the final solutions obtained by the CS are superior compared with the best solutions obtained by the other algorithms. Finally, the unique search features used in the CS and the implications for future researches are discussed in detail. Copyright © 2012 John Wiley & Sons, Ltd.
Based on the big data of multi-source observation of the underwater environment of the Hong Kong-Zhuhai-Macao Bridge,this study constructed an underwater three-dimensional(3D) scene with multi-source data fusion,realized the visual presentation and management of the underwater environment of large structures,and satisfied the requirements of visual operation and safety detection and protection of large structures.In this paper,the key technologies related to multisource spatio-temporal big data fusion and 3D real scene visualization were studied,a multi-storage distributed storage framework for hybrid spatio-temporal big data is constructed,a hierarchical organization model for spatio-temporal big data is proposed,and multi-source observation data fusion of large underwater structures is realized.Furthermore,3D scenes are rendered based on technologies such as WebGL,onshore/undersea terrain simulation,and gridding to realize 3D real-world visualization.The construction of a 3D real scene visualization model based on multi-source spatiotemporal big data fusion can quickly realize the deformation monitoring and spatiotemporal deduction of the Hong Kong-Zhuhai-Macao Bridge.Based on the fused 3D scene,the evolution analysis of underwater terrain and stratum can be conducted,which can effectively support the monitoring and management of the underwater environment of large structures.
Networks have increased rapidly both in scale and speed. Problems related to the control and management are of increasing interest. The average throughput and end-to-end delay of a network flow are important design factors. However, there is no satisfactory tool to obtain such parameters. The traditional packet-by-packet event driven simulation is slow when the network speed is high. The time driven simulation faces the difficulty of choosing the right time interval when simulating packet-switched networks. As the Transmission Control Protocol (TCP) is the most widely used transport layer protocol, and it uses a window based flow control mechanism, classic queuing theories involving Markov chain assumptions are not applicable. This paper describes a model for window based flow control packet-switched networks. The model attempts to provide a way to obtain the steady state results for large and high speed networks using TCP. We discuss in detail the construction, implementation and application of the model. This paper also compares the results obtained from the model with those from the packet-by-packet event driven simulation. The comparison shows the model is correctly modeling the networks.
No abstract is provided for this article.
No abstract is provided for this article.
Though nature-inspired algorithms have been shown to be effective, we still lack some in-depth understanding of these algorithms. This chapter attempts to provide a unified framework to analyze algorithms from different perspectives with some mathematical rigor. Both convergence and stability are analyzed, together with some algorithmic complexity. Some key issues concerning benchmarking and comparison of nature-inspired algorithms are also highlighted.
Editorial: Special issue on Metaheuristics in Artificial Intelligence By Guest Editors-in-Chief : Xin-She Yang,Suash Deb and Ping-Feng Pai
An integrated part of modern design practice in both engineering and industry is simulation and optimization. Significant challenges still exist, though huge progress has been made in the last few decades. This 5th workshop on Computational Optimization, Modelling and Simulation (COMS 2014) at ICCS 2014 will summarize the latest developments of optimization and modelling and their applications in science, engineering and industry. This paper reviews the past developments, the stateof-the-art present and the future trends, while highlighting some challenging issues in these areas. It can be expected that future research should focus on the data intensive applications, approximations for computationally expensive methods, combinatorial optimization, and large-scale applications.
