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Scheduling of manufacturers based on chaos optimization algorithm in cloud manufacturing

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2019年 58卷 13-20页

作者： Hu, Yanjuan Zhu, Feifan Zhang, Lin Lui, Yongkui Wang, Zhanli Changchun Univ Technol Sch Mechatron Engn Changchun 130012 Jilin Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Xidian Univ Sch Mechanoelect Engn Ctr Smart Mfg Syst Xian 710071 Shaanxi Peoples R China

With the rapid development of cloud manufacturing (CMfg) technology in Industrial Internet based on the concept of manufacturing as a service, how to effectively and quickly implement manufacturer scheduling in a cloud manufacturing environment has aroused widespread attention of researchers. Manufacturers in the cloud manufacturing environment are virtualized and digitized, and then aggregated in the form of cloud data. As a direct provider of cloud manufacturing services, manufacturers shift the service mode from the traditional de central type to a centralized type. However, in practice, manufacturers can't respond promptly to the needs of customer. The scheduling of manufacturers will directly affect the quality of cloud manufacturing services. This paper research the problem of manufacturer scheduling in the cloud manufacturing environment and analyzes the factors that affect the manufacturer resource scheduling in five categories including task load degree, task reliability, manufacturing efficiency, manufacturing resource richness and Internet of Things (IoT) match degree. At the same time, we establishes the scheduling index and the objective function model. The chaos optimization algorithm (COA) is used to solve the objective function and achieve scheduling of manufacturers under different scheduling tasks. The simulation results show that the proposed scheduling index is comprehensive and effective. Based on the math model of manufacturer scheduling, all the factors that influence the manufacturer scheduling in the cloud manufacturing environment can be merged together, and the complicated scheduling problem also can be transformed into the mathematical problem to solve. In this paper, the manufacturer scheduling algorithm based on chaos Theory can finish the scheduling of manufacturers under various tasks and make the cloud manufacturing platform provide manufacturing services to users in time.

关键词： Cloud manufacturing Manufacturer Scheduling chaos optimization algorithm AHP

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An improved chaos optimization algorithm-based parameter identification of synchronous generator

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ELECTRICAL ENGINEERING 2012年第3期94卷 147-153页

作者： Zhu, Qing Yuan, Xiaofang Wang, Hui Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China

This paper proposes an improved chaos optimization algorithm (ICOA)-based parameter identification approach of synchronous generator. The proposed ICOA is the combination of mutative-scale parallel chaos optimization algorithm and simplex search method. The parameter identification of synchronous generator is considered as an optimization process with a fitness function minimizing the errors between the estimated values and measured values, and the proposed ICOA will search the optimal parameters values of the plant. Simulation results have show the effective performance of the proposed parameter identification approach.

关键词： chaos optimization algorithm Parameter identification Synchronous generator Simplex search method

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Hybrid chaos optimization algorithm with artificial emotion

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APPLIED MATHEMATICS AND COMPUTATION 2012年第11期218卷 6585-6611页

作者： Yang, Yimin Wang, Yaonan Yuan, Xiaofang Yin, Feng Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China

Much research on Artificial Intelligence (AI) has been focusing on exploring various potential applications of intelligent systems. In most cases, the researches attempt to model human intelligence by mimicking the brain structure and function, but they ignore an important aspect in human learning and decision making: the artificial emotion. In this paper, we present a new unconstrained global optimization method, hybrid chaos optimization algorithm with artificial emotion (HCOAAE), which avoids trapping to local minima, and improves convergence in large space and high-dimension optimization problems. The main purpose of artificial emotion is to mimic decision making behavior process of humans, to choose most suitable parameters of HCOAAE and decide whether to change current search strategy or not in the next iteration. Numerical simulations of 13 benchmark functions with different dimensions are used to test the performance of HCOAAE. Experimental results show that the proposed method significantly outperforms the existing methods in terms of convergence speed, computational effectiveness, and numerical stability. Crown Copyright (C) 2011 Published by Elsevier Inc. All rights reserved.

关键词： chaos optimization algorithm Artificial emotion High-dimension optimization problem Unconstrained global optimization Electromagnetism-like mechanism algorithm

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Numerical Simulation of a Multi-Output Radar Orthogonal Waveform Based on a chaos optimization algorithm

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RUSSIAN PHYSICS JOURNAL 2022年第9期64卷 1599-1612页

作者： Sun, Caifeng Lopez, Miguel A. Shanxi Datong Univ Coll Phys & Elect Sci Datong Peoples R China Univ Castilla La Mancha Polytech Sch Cuenca Dept Math Cuenca Spain Univ Castilla La Mancha Inst Appl Math Sci & Engn IMACI Cuenca Spain

Aiming at problems of low probability of interception and poor anti-jamming performance of the multi-output radar, the numerical simulation based on a chaos optimization algorithm is proposed. Firstly, chaotic frequency coding is applied to the multi-output radar signal, and different frequency modulation methods are applied to different subpulses. At the same time, in view of the low efficiency of the numerical simulation algorithm in large space and high dimensional optimization, the GASA algorithm is used to increase the diversity of chaotic optimization algorithm search process. According to the specific working mode, the initial phase of each cycle of the multi-output radar orthogonal waveform is obtained, and the number of numerical simulations of multi-output radar orthogonal waveforms is established by the Model. Experimental results show that the proposed method can improve the radar energy utilization and signal-to-noise ratio, allocate reasonably the transmitting energy, and keep the structural stability of the LFM signal frequency changing continuously with time.

关键词： numerical simulation chaos optimization algorithm MIMO radar

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Nonlinear network disturbance suppression based on chaos optimization algorithm

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2023年第1期14卷 110-119页

作者： Zhang, Zefeng Chen, Kan Xinyang Vocat & Tech Coll Xinyang 464000 Peoples R China

Because the existing methods do not consider the random data packet loss problem, there is a large test error, and the problem of non-static disturbance suppression cannot be achieved. For this reason, a nonlinear network disturbance suppression method based on chaos optimization algorithm is proposed. Given the basic structure of the nonlinear network control system, it is concluded that the nonlinear network is mainly affected by uplink interference and downlink interference. A class of nonlinear network control systems with random packet loss data is studied. The protection entropy is obtained to monitor the packet loss data. Finally, a chaos optimization algorithm is used to suppress nonlinear network disturbances. The experimental results show that the proposed method can effectively suppress the disturbance under the uplink interference and downlink interference, and the test error is relatively small, the mean square error is 0.29, the maximum positive error is 0.521, and the maximum negative error is 0.21, which shows that the method is effective and can eliminate the influence of interference factors on the stability of nonlinear network.

关键词： chaos optimization algorithm Nonlinear network Disturbance suppression Packet loss data Protection entropy

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A new adaptive mutative scale chaos optimization algorithm and its application

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控制理论与应用（英文版） 2008年第2期6卷 141-145页

作者： Jiaqiang E Chunhua WANG Yaonan WANG Jinke GONG College of Mechanical and Automotive Engineering Hunan University Changsha Hunan 410082 China College of Electrical and Informational Engineering Hunan University Changsha Hunan 410082 China

Based on results of chaos characteristics comparing one-dimensional iterative chaotic self-map x = sin（2/x） with infinite collapses within the finite region[-1, 1] to some representative iterative chaotic maps with finite collapses （e.g., Logistic map, Tent map, and Chebyshev map）, a new adaptive mutative scale chaos optimization algorithm （AMSCOA） is proposed by using the chaos model x = sin（2/x）. In the optimization algorithm, in order to ensure its advantage of speed convergence and high precision in the seeking optimization process, some measures are taken： 1） the searching space of optimized variables is reduced continuously due to adaptive mutative scale method and the searching precision is enhanced accordingly; 2） the most circle time is regarded as its control guideline. The calculation examples about three testing functions reveal that the adaptive mutative scale chaos optimization algorithm has both high searching speed and precision.

关键词： Adaptive Mutative scale chaos optimization algorithm One-dimensional iterative chaotic self-map

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An improved chaos optimization algorithm and its application in the economic load dispatch problem

An improved chaos optimization algorithm and its application...

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2nd International Conference on Dynamics, Vibration and Control

作者： Han, Fang Lu, Qi-Shao Beijing Univ Aeronaut & Astronaut Sch Sci Beijing 100083 Peoples R China

This paper reforms the Mutative Scale chaos optimization algorithm (MSCOA). Numerical simulation demonstrates that the efficiency and performance of the algorithm are improved. An analysis of the Improved Mutative Scale chaos optimization algorithm (IMSCOA) is also given. IMSCOA is applied to examples of economic load dispatch, considering both the valve point effect and transmission loss. The results are compared with those computed by other methods, including MSCOA and another effective chaos algorithm - CROA. It is shown that IMSCOA provides more optimal results than the other methods, whether or not the problem is large scale. This demonstrates the efficiency and practicability of IMSCOA in engineering practice.

关键词： chaos optimization algorithm economic load dispatch IMSCOA valve point effect transmission loss

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Study on Minimum Zone Evaluation of Flatness Errors Based on a Hybrid chaos optimization algorithm

Study on Minimum Zone Evaluation of Flatness Errors Based on...

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5th International Conference on Intelligent Computing

作者： Zhang, Ke Shanghai Inst Technol Sch Mech & Automat Engn Shanghai 200235 Peoples R China

ISBN: (纸本)9783642040696

In this paper, according to characteristics of flatness error evaluation, a hybrid evaluation method to evaluate the minimum zone error is provided. The evolutional optimum model and the calculation process are introduced in detail. The hybrid optimization algorithm is based upon chaos optimization algorithm (COA) and Powell search. Compared with conventional optimum methods such as simplex search and Powell method, it can find the global optimal solution, and the precision of calculating result is very good. Moreover, the efficiency of COA is much higher than some stochastic algorithms such as simulated anneal algorithm and genetic algorithm (GA) when COA is used to a kind of continuous problems. The hybrid optimization algorithm can improve the efficiency of searching in the whole field by gradually shrinking the area of optimization variable. Finally, the control experiment results evaluated by different method such as the least square, simplex search, Powell optimum methods and GA, indicate that the proposed method does provide better accuracy on flatness error evaluation, and it has fast convergent speed as well as using computer expediently and popularizing application easily.

关键词： Flatness Evaluation chaos optimization algorithm Minimum Zone

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Image Segmentation Based on Two-Dimensional Inter-Class Cross Entropy and chaos optimization algorithm

Image Segmentation Based on Two-Dimensional Inter-Class Cros...

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International Forum on Information Technology and Applications (IFITA 2009)

作者： Zhang Xinming Zhang Huiyun Henan Normal Univ Coll Comp & Informat Technol Xinxiang 453007 Peoples R China

ISBN: (纸本)9780769536002

In this paper, a thresholding technique based on two-dimensional inter-class cross entropy and chaos optimization algorithm (COA) is presented. Firstly, adopt the cross entropy approach to describe the difference in pixel information between the object and the background in a two-dimensional histogram and to use maximum inter-class separation degree. Then apply improved COA to get the threshold value, which can get global solution with low computational load. Experimental results show the proposed approach is effective and gets competitive visual effects.

关键词： image segmentation two-dimensional cross entropy chaos optimization algorithm thresholding

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Solving Robust Reliability Index Based on the Mutative Scale chaos optimization algorithm

Solving Robust Reliability Index Based on the Mutative Scale...

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2nd Global Conference on Civil, Structural and Environmental Engineering (GCCSEE 2013)

作者： Zhang Feng He Xindang Nan Hua Ren Hao Northwestern Polytech Univ Sch Mech Civil Engn & Architecture Xian 710129 Peoples R China

ISBN: (纸本)9783037859261

A novel method based on the mutative scale chaos optimization algorithm is proposed to solve the robust reliability index of non-probabilistic reliability model. Compared with the basic chaos optimization method, this novel method can minimize searching area of optimization variable and change the adjustable parameters of next search stage for improving the optimization performance. The proposed optimization algorithm is more efficient and has smaller computational complexity in solving robust reliability index. The feasibility and efficiency of the proposed method are demonstrated by two examples.

关键词： non-probabilistic reliability model robust reliability index mutative scale chaos optimization algorithm

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