Analysis and Improvement of Fireworks Algorithm

Li, Xiguang; Han, Shoufei; Cheng, Gong

doi:10.3390/a10010026

Cited by 21 publications

(8 citation statements)

References 18 publications

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“…It has characteristics like fast convergence and reaching global optima. Analysis and improvement of FWA is discussed by authors in [23]. A cooperative framework for fireworks algorithm is proposed by authors in [24].…”

Section: Related Studiesmentioning

confidence: 99%

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A fireworks algorithm based Pi-Sigma neural network (FWA-PSNN) for modelling and forecasting chaotic crude oil price time series

Nayak¹

2018

EAI Endorsed Transactions on Energy Web

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Capturing the complex correlations among the data on the crude oil price time series is challenging, hence accurate prediction of it is difficult. Contrast to multilayer artificial neural network, Pi-Sigma neural network (PSNN) is characterized with stronger approximation ability, fast learning and higher fault tolerance. Fireworks algorithm (FWA) is a new metaheuristic motivated from the occurrence of fireworks explosion, characterized with fast convergence capability, parallelism and finds global optima. This article intends to achieve the synergetic effect of both on hybridizing them. It uses FWA for optimization of weight and bias of PSNN (FWA-PSNN) and overcomes the limitations of gradient based training. It has single hidden layer structure and trainable weight, hence fast and robust. The FWA-PSNN is evaluated on prediction of crude oil price time series. Extensive simulation results, performance analysis, and statistical significance test suggested the suitability of FWA-PSNN.

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Section: Related Studiesmentioning

confidence: 99%

“…However its application toward crude oil price time series is limited. Analysis and improvement of fireworks algorithm is suggested by authors in [23]. A cooperative framework for FWA is suggested in [24].…”

Section: Introductionmentioning

confidence: 99%

A fireworks algorithm based Pi-Sigma neural network (FWA-PSNN) for modelling and forecasting chaotic crude oil price time series

Nayak¹

2018

EAI Endorsed Transactions on Energy Web

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“…The algorithm will run until a defined ending criteria is met; either the maximum number of iterations or the accuracy requirement of the problem. The components within the fireworks algorithm are designed to adopt the behavior of the real counterparts: the explosion operation, the mutation operation, the mapping rule and the selection strategy [6], [7].…”

Section: B Foundations Of the Firework Algorithmmentioning

confidence: 99%

Object-Oriented Research Framework for the Fireworks Algorithm with the Focus on the Travelling Salesman Problem

Ehni¹,

Müller²

2018

IJCTE

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The fireworks algorithm is a lately developed algorithm based on fireworks in the night sky. It is a swarm intelligence algorithm with a broad range of use. In this paper the algorithm is introduced and discussed. Furthermore, an implementation of the algorithm for optimizing the travelling salesman problem is introduced. Prior to implementation the adjustments to the algorithm will be provided. The implementation is based on Java and the layer based and extendable architecture of the implemented application is introduced. The performance of the implementation and the impact of the parameters on the behavior of the algorithm will be tested and analyzed. The results show that the fireworks algorithm is a efficient and performant algorithm to optimize the combinatorial problem of the travelling salesman.

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“…Assignment and scheduling task and jobs are two sub-problem in FJSP and there are several objectives such as minimization make-span time, and minimization total idle time [1,17]. These objectives most widely studied and there many dataset used for this problem such as Hurink-Data deal with this problem and widely used [7].…”

Section: Introductionmentioning

confidence: 99%

Solving Job Scheduling Problem Using Fireworks Algorithm

Hasoon¹,

Hassan²

2019

J. Al-Qadisiyah Comp. Sci. Math.

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Scheduling is critical part in most creation frameworks and information processing as sequencing of tasks or jobs framework executed on a grouping of processors. One of the NP-hard problem is “Job Shop Scheduling Problem”. In this work, a method of optimization proposed called “Fireworks Algorithm”. The solutions divided into fireworks and each one applied sparks to find the best solution. For some selected spark applied Gaussian mutation to find enhanced solution and find optimum solution. FWA tested on dataset to improve performance and it do well with respect to some other algorithm like Meerkat Clan Algorithm (MCA), Camel Herds Algorithm) CHA(, and Cukoo Search Algorithm (CSA).

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Analysis and Improvement of Fireworks Algorithm

Cited by 21 publications

References 18 publications

A fireworks algorithm based Pi-Sigma neural network (FWA-PSNN) for modelling and forecasting chaotic crude oil price time series

A fireworks algorithm based Pi-Sigma neural network (FWA-PSNN) for modelling and forecasting chaotic crude oil price time series

Object-Oriented Research Framework for the Fireworks Algorithm with the Focus on the Travelling Salesman Problem

Solving Job Scheduling Problem Using Fireworks Algorithm

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