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fireworks algorithm for mean-VaR/CVaR models

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2017年 483卷 1-8页

作者： Zhang, Tingting Liu, Zhifeng Tianjin Univ Coll Management & Econ Tianjin 300072 Peoples R China Hainan Univ Sch Econ & Management Haikou 570228 Peoples R China

Intelligent algorithms have been widely applied to portfolio optimization problems. In this paper, we introduce a novel intelligent algorithm, named fireworks algorithm, to solve the mean-VaR/CVaR model for the first time. The results show that, compared with the classical genetic algorithm, fireworks algorithm not only improves the optimization accuracy and the optimization speed, but also makes the optimal solution more stable. We repeat our experiments at different confidence levels and different degrees of risk aversion, and the results are robust. It suggests that fireworks algorithm has more advantages than genetic algorithm in solving the portfolio optimization problem, and it is feasible and promising to apply it into this field. (C) 2017 Elsevier B.V. All rights reserved.

关键词： fireworks algorithm Portfolio optimization Genetic algorithm Value at risk

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A weighted pattern matching approach for classification of imbalanced data with a fireworks-based algorithm for feature selection

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CONNECTION SCIENCE 2019年第2期31卷 143-168页

作者： Sreeja, N. K. PSG Coll Technol Dept Appl Math & Computat Sci Coimbatore Tamil Nadu India

Learning a classifier from imbalanced data is a challenging problem in Machine learning. A dataset is said to be imbalanced when the number of instances belonging to one class is much less than the number of instances belonging to the other class. Classifiers that proves efficient on standard data fail when the data is imbalanced as they are over trained by the majority class instances. Since class imbalance is a common characteristic of real-world data, the need for better classifiers becomes essential. This paper proposes a novel instance-based classification algorithm called Weighted Pattern Matching based Classification (PMC+) for classifying imbalanced data. PMC+ classifies unlabelled instances by computing the absolute difference between the feature values of the instances in the dataset and the unlabelled instance. PMC+ employs a simple classification procedure with weights and shows reasonably good performance. To improve the performance of PMC+, fireworks based Feature and Weight Selection algorithm based on the idea of PMC+ has been proposed. PMC+ is evaluated on 44 binary imbalanced datasets and 15 multiclass imbalanced datasets. Although PMC+ does not employ a resampling or cost-sensitive method, experiments show that PMC+ is effective for classification of imbalanced data. The results of the experiments were validated using various non-parametric statistical tests.

关键词： Classification pattern matching fireworks algorithm imbalanced data

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Image retrieval based on fireworks algorithm optimizing convolutional neural network 4

Image retrieval based on fireworks algorithm optimizing conv...

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4th IEEE International Symposium on Wireless Systems within the International Conferences on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS-SWS)

作者： Wang, Chunzhi Wu, Pan Yan, Lingyu Zhou, Fangyu Cai, Wencheng Hubei Univ Technol Sch Comp Sci Wuhan Hubei Peoples R China

ISBN: (纸本)9781538675878

For the problem of the slow convergence rate of the traditional CNN algorithm using gradient descent algorithm to optimize parameters, a CNN model based on fireworks algorithm optimization is proposed, the parameters that need to be optimized are used as the input to the fireworks algorithm, and the cross-entropy (error) is used as the fitness function to improve the tuning process in the backward propagation, the MNIST handwritten character set is used for simulation experiments of image retrieval. The results show that the convergence speed of the improved algorithm is significantly improved.

关键词： fireworks algorithm convolutional neural network gradient descent image retrieval

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A Novel Mixed-Variable fireworks Optimization algorithm for Path and Time Sequence Optimization in WRSNs 13th

A Novel Mixed-Variable Fireworks Optimization Algorithm for ...

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13th European-Alliance-for-Innovation (EAI) International Conference on Communications and Networking in China (ChinaCom)

作者： Xia, Chengkai Wei, Zhenchun Lyu, Zengwei Wang, Liangliang Liu, Fei Feng, Lin Hefei Univ Technol Sch Comp & Informat Hefei Peoples R China Minist Educ Engn Res Ctr Safety Crit Ind Measurement & Contro Hefei Peoples R China Key Lab Ind Safety & Emergency Technol Hefei Anhui Peoples R China

ISBN: (纸本)9783030061616;9783030061609

To prolong the lifespan of the network, the auxiliary charging equipment is introduced into the traditional Wireless Sensor Networks (WSNs), known as Wireless Rechargeable Sensor Networks (WRSNs). Different from existing researches, in this paper, a periodic charging and data collecting model in WRSNs is proposed to keep the network working perpetually and improve data collection ratio. Meanwhile, the Wireless Charging Vehicle (WCV) has more working patterns, charging, waiting, and collecting data when staying at the sensor nodes. Then, the simultaneous optimization for the traveling path and time sequence is formulated to be a mixed-variable optimization problem. A novel Mixed-Variable fireworks Optimization algorithm (MVFOA) is proposed to solve it. A large number of experiments show the feasibility of the MVFOA, and MVFOA is superior to the Greedy algorithm.

关键词： Wireless rechargeable sensor networks Mixed-variable optimization fireworks algorithm

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Logistics Distribution Path Planning Based on fireworks Differential algorithm

Logistics Distribution Path Planning Based on Fireworks Diff...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Dan Chen Xiaoyong Zhang Dianzhu Gao Kai Gao Mengfei Wen Zhiwu Huang School of Automation Central South University Changsha China School of Computer Science and Engineering Central South University Changsha China College of Automotive and Mechanical Engineering Changsha University of Science and Technology Changsha China Changsha College for Preschool Education Changsha China

ISBN: (数字)9781728185262

ISBN: (纸本)9781728185279

Logistics distribution is an important link in logistics. Whether the logistics distribution path can be effectively optimized will directly affect the efficiency of the logistics distribution system. To plan the logistics distribution path reasonably, to reduce the cost of logistics management, for the multi-object path planning problem in logistics distribution, the fireworks differential evolution algorithm is used to design an optimization scheme. To achieve the overall goal of saving logistics and distribution costs, real number coding is used for each distribution point, and actual road information is obtained through the Gaode API. Aiming at the defects of the standard fireworks algorithm, the differential evolution algorithm is introduced based on the fireworks algorithm to plan the distribution route. The simulation results show that the firework differential evolution algorithm can effectively plan the optimal distribution path, and compared with the original firework algorithm, the ant colony algorithm and particle swarm optimization algorithm have a better improvement in the optimization accuracy.

关键词： fireworks algorithm Simulation Roads Path planning Particle swarm optimization Optimization Logistics

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Task scheduling algorithm based on fireworks algorithm

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2018年第1期2018卷 1页

作者： Li, Jingmei Tian, Qiao Zhang, Guoyin Wu, Weifei Xue, Di Li, Lanting Wang, Jiaxiang Chen, Lei Harbin Engn Univ Coll Comp Sci & Technol Harbin Heilongjiang Peoples R China Georgia Southern Univ Statesboro GA USA

To give full play to the high efficiency and parallelism of multi-processor systems, the fireworks algorithm (FWA) is improved, and a multi-processor task scheduling algorithm based on improved FWA, named IMFWA, is proposed. IMFWA maps continuous space to discrete space by designing the fireworks location coding method, improves the Gaussian mutation process, and sets adaptive dimensions to accelerate the convergence speed of the algorithm. At the same time, in order to reduce the time complexity of the algorithm and shorten the time finding the optimal task scheduling sequence, the fitness-based tournament selection strategy is used instead of the rule based on Euclidean distance. Finally, IMFWA is compared with the basic fireworks algorithm and the genetic algorithms on the Matlab platform for performance analysis. The results show that the IMFWA has advantages in the convergence speed, and the negative impact of the number of tasks is also lower than the fireworks algorithm and genetic algorithm.

关键词： Task scheduling fireworks algorithm Gaussian mutation Adaptive

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Spectrum allocation for cognitive radio networks using the fireworks algorithm

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COMPUTER SYSTEMS SCIENCE AND ENGINEERING 2018年第4期33卷 275-286页

作者： Zhou Feng Xue Weilian Liaoning Normal Univ Sch Management Dalian 116029 Peoples R China

The fireworks algorithm features a small number of parameters, remarkable optimization ability, and resistance to a local optimum. Based on the graph coloring model, the fireworks algorithm is introduced for the first time to solve the spectrum allocation problem for cognitive radio networks, thus maximizing utility and fairness of spectrum allocation. Two-layer binary coding is adopted for individual fireworks. The first layer refers to the coding of cognitive users used to determine channels that can be connected with the user. The second layer refers to the auxiliary coding of channels responsible for addressing mutual interference among multiple cognitive users when they connect with the same channel at the same time. Explosion operator, mutation operator, and the selection operation are designed to allocate the spectrum for the cognitive radio network. Simulation results demonstrate superiority and efficiency of the proposed algorithm in terms of spectrum allocation

关键词： fireworks algorithm spectrum allocation system utility system fairness

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An effective fireworks algorithm for warehouse-scheduling problem

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2017年第1期39卷 75-85页

作者： Ye, Sengang Ma, Haiping Xu, Sheng Yang, Wenqiang Fei, Minrui Shaoxing Univ Dept Elect Engn Shaoxing Zhejiang Peoples R China Shanghai Univ Sch Mechatron Engn & Automat Shanghai Key Lab Power Stn Automat Technol Shanghai Peoples R China Henan Normal Univ Sch Comp & Informat Engn Xinxiang Henan Peoples R China

This paper proposes an effective fireworks algorithm (FWA), which is a new heuristic algorithm inspired by the phenomenon of a fireworks display, to solve the warehouse-scheduling problem. First, a real-world warehouse-scheduling problem is described in detail, and it is formulated as a constrained single-objective optimization problem. Then an effective FWA, FWA-LSCM, is developed by combining with a local search method and chaotic mutation, which are used to balance the exploration and exploitation of FWA. The experimental results show that FWA-LSCM is a competitive algorithm for a set of 2013 Congress on Evolutionary Computation (CEC) benchmark functions. Finally, the proposed FWA-LSCM is successfully applied to the warehouse-scheduling problem and outperforms other FWA algorithms studied in this paper.

关键词： fireworks algorithm heuristic algorithm local search travel time analysis warehouse scheduling

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Determination of Johnson-Cook material model parameters by an optimization approach using the fireworks algorithm

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Procedia Manufacturing 2018年 22卷 107-113页

作者： Nikolaos E. Karkalos Angelos P. Markopoulos National Technical University of Athens Heroon Polytechniou 9 Athens 15780 Greece

The accurate description of materials behavior is essential when investigating the application of these materials in the industrial practice. For this purpose, experimental data are fitted to suitable constitutive laws using various methods. In this paper, the determination of Johnson Cook material model parameters for AISI 316L stainless steel is performed using an optimization approach. More specifically, the fireworks algorithm is employed to determine the appropriate material parameters for AISI 316L steel. The results indicate a sufficient performance of the optimization approach, which can be further developed and applied for other types of materials as well.

关键词： stress-strain relationship Johnson-Cook material model artificial intelligence fireworks algorithm optimization AISI 316L stainless steel

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Optimization of economic/environmental operation management for microgrids by using hybrid fireworks algorithm

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2017年第12期27卷 n/a-N.PAG页

作者： Wang, Zhenyu Zhu, Qibing Huang, Min Yang, Bao Jiangnan Univ Minist Educ Key Lab Adv Proc Control Light Ind Wuxi 214122 Peoples R China Oakland Univ Dept Elect & Comp Engn Rochester MI 48309 USA

The wide use of renewable energy sources stimulates the implementation of microgrid (MG) systems. MG is an independent power system that consists of various distributed generations (DGs), storage devices, and loads. The optimization problems of MG have gained wide spread interest considering the economic and environmental operation management of the system. To address the multi-variable non-linear programming problem with multiple hybrid constraints, this paper proposes a novel hybrid multi-objective fireworks algorithm with gravitational search operator (MFAGSO). In the algorithm, the operator, as a new search mechanism, directs the sparks in the clustered region to exchange positional information with Pareto-optimal solutions at each iteration process for obtaining accurate results. The operation management of typical grid-connected MG, which comprises various DGs and storage battery, was optimized within 24hours to evaluate the performance of the proposed algorithm. Considering operation cost and pollutant emission individually or simultaneously, 3 scenarios were involved in operation management for power market planning and practical considerations. The simulation results of the proposed algorithm were compared with those from other methods employed in previous literature and original fireworks algorithm. The results demonstrated the superior performance of the proposed method to solve operation management for optimizing problems of MG.

关键词： economic and environmental operation management fireworks algorithm gravitational search microgrid multi-objective optimization

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