Firefly algorithm is one of the evolutionary optimization algorithms, and is inspired by fireflies behavior in nature. Each firefly movement is based on absorption of the other one. In this paper to stabilize firefly’s movement, it is proposed a new behavior to direct fireflies movement to global best if there was no any better solution around them. In addition to increase convergence speed it ...

Many metaheuristic algorithms are nature-inspired, and most are population-based. Particle swarm optimization is a good example as an efficient metaheuristic algorithm. Inspired by PSO, many new algorithms have been developed in recent years. For example, firefly algorithm was inspired by the flashing behaviour of fireflies. In this paper, the author extends the standard firefly algorithm furth...

Data acquisition is the foundation of soft sensor and data fusion. Distributed data acquisition and its synchronization are the important technologies to ensure the accuracy of soft sensors. As a research topic in bionic science, the firefly-inspired algorithm has attracted widespread attention as a new synchronization method. Aiming at reducing the design difficulty of firefly-inspired synchro...

Optimum design of steel frames is a complicated process because the designer has to consider a large number of nonlinear constraints which are imposed by steel design codes while also dealing with discrete design variables. Obtaining the optimum solution to discrete programming problems was never easy until the emergence of metaheuristic techniques. The firefly algorithm, one of the recent meta...

This paper proposes a meta-heuristic Multi-Population Firefly Algorithm (MPFA) for single-modal optimization using two multi-population models, i.e., one is based on the island model while the other on the mainland-island model. The unique characteristics of each sub-population is evolved independently and the diversity of the entire population is effectively increased. Sub-populations communic...

Recently huge amount of data is available in the field of medicine that helps the doctors in diagnosing diseases when analysed. Data mining techniques can be applied to these medical data to extract knowledge so that disease prediction becomes accurate and easier. In this work, cardiotocogram (CTG) data is analysed using Support Vector Machine (SVM) for predicting fetal risk. Opposition based f...