The COVID-19 pandemic and competitiveness pressure the pharmaceutical companies to acquire systems designed be as reliable possible. present paper aims optimize design of a plant through reliability allocation heterogeneous components under constraints. problem is solved by resorting three nature-inspired algorithms artificial intelligence (AI): grey wolf optimizer (GWO), shuffled frog-leaping ...

In this work, we present a multi-phase hybrid algorithm based on clustering to solve the multi-depots vehicle routing problem (MDVRP). The proposed algorithm initially adopts K-means algorithm to execute the clustering analyses, which take the depots as the centroids of the clusters, for the all customers of MDVRP, then implements the local depth search using the Shuffled Frog Leaping Algorithm...

The flexible job shop scheduling problem is a well-known combinatorial optimization problem. This paper proposes an improved shuffled frog-leaping algorithm to solve the flexible job shop scheduling problem. The algorithm possesses an adjustment sequence to design the strategy of local searching and an extremal optimization in information exchange. The computational result shows that the propos...

Microarray technology is universally used in the study of disease diagnosis using gene expression levels. The main shortcoming of gene expression data is that it includes thousands of genes and a small number of samples. Abundant methods and techniques have been proposed for tumor classification using microarray gene expression data. Feature or gene selection methods can be used to mine the gen...

This paper shows the results obtained in the analysis of the impact of Distributed Generation (DG) on distribution losses and presents a new algorithm to the optimal allocation of distributed generation resources in distribution networks. The optimization is based on a Shuffled Frog Leaping Algorithm (SFLA) aiming to optimal DG allocation in distribution network. Shuffled frogleaping algorithm ...

Shuffled leap frog algorithm (SFLA) is a new nature-inspired intelligent algorithm, which uses the whole update and evaluation strategy on solutions. For solving multi-dimension function optimization problems, this strategy will deteriorate the convergence speed and the quality of solution of algorithm due to interference phenomena among dimensions. To overcome this shortage, a dimension by dim...

Measurement of magnitude and frequency of the voltage flicker is very important for monitoring andcontrolling voltage flicker efficiently to improve the network power quality. This paper presents twonew methods for measurement of flicker signal parameters using Shuffled Frog Leaping Algorithm(SFLA) and Imperialist Competitive Algorithm (ICA). This paper estimates fundamental voltage andflicker ...

In data mining, association rule mining is a popular and well researched method for discovering interesting relations between variables in large databases, which are meaningful to the users and can generate strong rules on the basis of these frequent patterns, which are helpful in decision support system. Quantum Particle Swarm Optimization (QPSO) is one of the several methods for mining associ...