R. Vasundhara Devi

Work place: Department of Computer Science, Pondicherry University, Pondicherry, India

E-mail: vasu_devi@yahoo.com


Research Interests: Computer systems and computational processes, Artificial Intelligence, Evolutionary Computation, Swarm Intelligence, Data Structures and Algorithms, Algorithm Design


R. Vasundhara Devireceived M. Tech Degree from Pondicherry University. Currently pursuing Ph.D. Degree in Computer Science at Pondicherry University, Pondicherry, India. Her research interests include optimization algorithms, interdisciplinary applications, Databases and Data mining.

Author Articles
Multi-objective Monkey Algorithm for Drug Design

By R. Vasundhara Devi S. Siva Sathya Nilabh Kumar Mohane Selvaraj Coumar

DOI: https://doi.org/10.5815/ijisa.2019.03.04, Pub. Date: 8 Mar. 2019

Swarm intelligence algorithms are designed to mimic the natural behaviors of living organisms. The birds, animals and insects exhibit extraordinary problem solving behaviors and intelligence when living in colonies or groups. These unique behaviors form the basis for the design of the Metaheuristic which are helpful in solving several real-life combinatorial optimization problems. Monkey algorithm is developed based on the unique behaviors of monkeys such as mountain and tree climbing, jumping, watching and somersaulting. This paper reports for the first time the design and development of Multi-objective Monkey Algorithm (MoMA) and its use for the design of molecules with optimal drug-like properties. Finally, the performance of the proposed MoMA for Drug design (MoMADrug) is compared with the previously disclosed Multi-objective Genetic algorithm (MoGADdrug) for the design of drug-like molecules.

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Monkey Behavior Based Algorithms - A Survey

By R. Vasundhara Devi S. Siva Sathya

DOI: https://doi.org/10.5815/ijisa.2017.12.07, Pub. Date: 8 Dec. 2017

Swarm intelligence algorithms (SIA) are bio-inspired techniques based on the intelligent behavior of various animals, birds, and insects. SIA are problem-independent and are efficient in solving real world complex optimization problems to arrive at the optimal solutions. Monkey behavior based algorithms are one among the SIAs first proposed in 2007. Since then, several variants such as Monkey search, Monkey algorithm, and Spider Monkey optimization algorithms have been proposed. These algorithms are based on the tree or mountain climbing and food searching behavior of monkeys either individually or in groups. They were designed with various representations, covering different behaviors of monkeys and hybridizing with the efficient operators and features of other SIAs and Genetic algorithm. They were explored for applications in several fields including bioinformatics, civil engineering, electrical engineering, networking, data mining etc. In this survey, we provide a comprehensive overview of monkey behavior based algorithms and their related literatures and discuss useful research directions to provide better insights for swarm intelligence researchers.

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