Anuradha Ariyaratne

University of Sri Jayewardenepura · Department of Computer Science

Path finding is used to solve the problem of finding a traversable path through an environment with obstacles. This problem can be seen in many different fields of study and these areas rely on fast and efficient path finding algorithms. This paper aims to describe and review state of the art optimization techniques that are used on optimized path...

Separating a given data set into groups (clusters) based on their natural similar characteristics is one of the main concerns in data clustering. A cluster can be defined as a collection of objects which are “homogeneous” between them and are “heterogeneous” to the objects belonging to other clusters. Many areas encounter clustering based applicati...

This review explores the avenues for the application of meta-heuristics in sports. The necessity of sophisticated algorithms to investigate different NP hard problems encountered in sports analytics was established in the recent past. Meta-heuristics have been applied as a promising approach to such problems. We identified team selection, optimal l...

Multi-model optimization brings out the concept of finding all or most of the multiple solutions of a problem, as opposed to a single best solution. Recently many researches have focused on finding the capability of swarm intelligence and evolutionary algorithms in solving such mathematical problems. This paper proposes a hybrid algorithm combining...

The most acquainted methods to find root approximations of nonlinear equations and systems; numerical methods possess disadvantages such as necessity of acceptable initial guesses and the differentiability of the functions. Even having such qualities, for some univariate nonlinear equations and systems, approximation of roots is not possible with n...

The most acquainted methods to find root approximations of nonlinear equations and systems; numerical methods possess disadvantages such as necessity of acceptable initial guesses and the differentiability of the functions. Even having such qualities, for some univariate nonlinear equations and systems, approximations of roots is not possible with...

Most numerical methods that are being used to solve systems of nonlinear equations require the differentiability of the functions and acceptable initial guesses. However, some optimization techniques have overcome these problems, but they are unable to provide more than one root approximation simultaneously. In this paper, we present a modified fir...

Ant colony system (ACS) is a promising approach which has been widely used in problems such as Travelling Salesman Problems (TSP), Job shop scheduling problems (JSP) and Quadratic Assignment problems (QAP). In its original implementation, parameters of the algorithm were selected by trial and error approach. Over the last few years, novel approache...

Music has an influence on peoples' lives in various ways. Multi-track recording, auto tune and digital software are some of the advancements. All songs produced by musicians do not achieve similar popularity. This is because all songs do not satisfy user expectations. Thus there is a need to analyse the significant features that distinguish highly...

In this article, we are presenting a software solution that proposes some modifications to the existing firefly algorithm. The modification; archived firefly algorithm [AFFA] exhibits the ability of finding almost all complex roots of a given nonlinear equation within a reasonable range. The software implementation includes two main properties; an...

Existing numerical methods to solve univariate nonlinear equations sometimes fail to return the required results. We propose a modified firefly algorithm [MOD FA] with a self-tuning ability to solve a given univariate nonlinear equation. Our modification is capable of finding almost all real as well as complex roots of a nonlinear equation within a...

In this article, we are presenting a software solution that proposes some modifications to the existing firefly algorithm. The modification; archived firefly algorithm [AFFA] exhibits the ability of finding almost all complex roots of a given nonlinear equation within a reasonable range. The software implementation includes two main properties; an...

Nature inspired algorithms are modern AI related algorithms which embrace natural optimization techniques to build optimization algorithms. Now there can be seen a rapid development of these algorithms as well as applying the algorithms on complicated problems. Firefly Algorithm is one such algorithm that mimics the flashing behavior of fireflies....

Recently developed meta-heuristic algorithms such as firefly algorithm, bat algorithm, particle swarm optimization and harmony search are now becoming popular for providing nearly accurate solutions for tough optimization problems. This paper addresses the problem of finding all roots of a given uni-variate nonlinear equation with real and complex...

Numerical approaches that have been suggested to solve nonlinear equations most of the time require the derivative information of the desired equation and are capable of giving one approximation at a time. Bat inspired algorithm [BA] provides novel solutions for those problems. It does not use the derivative information of the equation and it consi...

Nature inspired algorithms for their powerfulness, acquire a unique place among the algorithms for optimization. This paper intends to provide a comparison of firefly algorithm (FA) with 3 other nature inspired algorithms; genetic algorithms (GA), particle swarm optimization algorithm (PSO) and ant colony systems (ACS). Traveling salesman problem (...