Bio-inspired algorithms become among the most powerful algorithms for optimization. In this paper, we intend to provide one of the recent bio-inspired metaheuristic which is the Firefly Algorithm (FF) to optimize power dispatching. For evaluation, we adapt the particle swarm optimization to the problem in the same way as the firefly algorithm. The application is done in an IEEE-14 and on two th...

One of the significant strategies of the power systems is Economic Dispatch (ED) problem, which is defined as the optimal generation of power units to produce energy at the lowest cost by fulfilling the demand within several limits. The undeniable impacts of ramp rate limits, valve loading, prohibited operating zone, spinning reserve and multi-fuel option on the economic dispatch of practical p...

Bio-inspired algorithms are widely used to optimize the model parameters of GRN. In this paper, focus is given to develop improvised versions of bio-inspired algorithm for the specific problem of reconstruction of gene regulatory network. The approach is applied to the data set that was developed by the DNA microarray technology through biological experiments in the lab. This paper introduced a...

This paper introduces a novel population-based bio-inspired meta-heuristic optimization algorithm, called Blood Coagulation Algorithm (BCA). BCA derives inspiration from the process of blood coagulation in human body. The underlying concepts and ideas behind proposed algorithm are cooperative behavior thrombocytes their intelligent strategy clot formation. These behaviors modeled utilized to un...

This paper proposes an ambitious bio-inspired algorithm for associative classification (AC) based on Quantum-Inspired Artificial Immune system (QAIS) for building an efficient classifier by searching association rules to find the best subset of rules for all possible association rules. it integrates concepts of quantum computing (QC) and artificial immune system (AIS) as a bio natural inspired ...

Recently several approaches have been presented that exploit the ability of Physarum polycephalum to connect several food sources via a network of pipes in order to maintain an efficient food distribution inside the organism. These approaches use the mechanisms found in nature in order to solve a technical problem, namely the design of constructing faulttolerant and efficient connection network...

The Flocking model, first proposed by Craig Reynolds, is one of the first bio-inspired computational collective behavior models that has many popular applications, such as animation. Our early research has resulted in a flock clustering algorithm that can achieve better performance than the Kmeans or the Ant clustering algorithms for data clustering. This algorithm generates a clustering of a g...