In this paper we present parallel implementation of genetic algorithm using map/reduce programming paradigm. Hadoop implementation of map/reduce library is used for this purpose. We compare our implementation with implementation presented in [1]. These two implementations are compared in solving One Max (Bit counting) problem. The comparison criteria between implementations are fitness converge...

in a large scale cyclic storage system ,as the number of rule parameters and/or number of operating period increase, general purpose gradient-based nlp solvers and/or genetic algorithms may loose their merits in finding optimally feasible solution to the problem. in these cases hybrid ga which decomposes the main problem into two manageable sub-problems with an iterative scheme between ga and l...

Clustering plays an important role in the decomposition of complex products structure. Different clustering algorithms may achieve different effects of the decomposition. This paper aims to proposes a bio-inspired genetic algorithm that is implemented based on its reliable fitness function and design structure matrix (DSM) for clustering analysis of complex products. This new bio-inspired genet...

UCTTP is a NP-hard problem, which must be performed for each semester frequently. The major technique in the presented approach would be analyzing data to resolve uncertainties of lecturers’ preferences and constraints within a department in order to obtain a ranking for each lecturer based on their requirements within a department where it is attempted to increase their satisfaction and develo...

Microarray gene expressions provide an insight into genomic biomarkers that aid in identifying cancerous cells and normal cells. In this study, functionally related genes are identified by partitioning gene data. Clustering is an unsupervised learning technique that partition gene data into groups based on the similarity between their expression profiles. This identifies functionally related ge...

in this paper, a new alternative method for order reduction of high order systems is presented based on optimization of multi objective fitness function by using harmony search algorithm. at first, step response of full order system is obtained as a vector, then, a suitable fixed structure considered for model order reduction which order of original system is bigger than fixed structure model. ...

This paper introduces two novel approaches to estimate the clique potentials in binary and multilevel realizations of Gibbs Markov random field (GMRF) models. The first approach employs a genetic algorithm (GA) in order to arrive at the closest synthesized image that resembles the original “observed” image. The Second approach is used to estimate the parameters of Gaussian Markov random field. ...