A.R. Hota

Publications (2)0 Total impact

• Conference Proceeding: An improved quantum-behaved Particle Swarm Optimization using fitness-weighted preferential recombination

  A. Pat, A.R. Hota
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  ABSTRACT: Quantum-behaved particle swarm optimization (QPSO) is a widely used algorithm for global optimization of multi-dimensional functions. In this paper, a modified and improved QPSO using fitness weighted recombination operator along with a fitness proportionate selection mechanism is proposed. The proposed algorithm is tested on different benchmark functions and compared with the standard Particle Swarm Optimization (PSO) and QPSO. The experimental results show comprehensive superiority of the proposed algorithm.
  Nature and Biologically Inspired Computing (NaBIC), 2010 Second World Congress on; 01/2011
• Source

  Available from: arxiv.org

  Conference Proceeding: An adaptive quantum-inspired differential evolution algorithm for 0–1 knapsack problem

  A.R. Hota, A. Pat
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  ABSTRACT: Differential evolution (DE) is a population based evolutionary algorithm widely used for solving multidimensional global optimization problems over continuous spaces. However, the design of its operators makes it unsuitable for many real-life constrained combinatorial optimization problems which operate on binary space. On the other hand, the quantum inspired evolutionary algorithm (QEA) is very well suitable for handling such problems by applying several quantum computing techniques such as Q-bit representation and rotation gate operator, etc. This paper extends the concept of differential operators with adaptive parameter control to the quantum paradigm and proposes the adaptive quantum-inspired differential evolution algorithm (AQDE). The performance of AQDE is found to be significantly superior as compared to QEA and a discrete version of DE on the standard 0-1 knapsack problem for all the considered test cases.
  Nature and Biologically Inspired Computing (NaBIC), 2010 Second World Congress on; 01/2011