Modified Lion Optimization Algorithm with Discrete Hopfield Neural Network for Higher Order Boolean Satisfiability Programming
Mansor, M. A., Kasihmuddin, M. S. M., and Sathasivam, S.
Corresponding Email: [email protected]
Received date: 15 January 2020
Accepted date: 30 July 2020
Abstract:
The Lion Optimization algorithm (LOA) and discrete Hopfield neural network (DHNN) are broadly employed for solving various complex optimization problems. Specifically, the Lion Optimization algorithm (LOA) is a new iterative and robust nature-inspired swarm metaheuristic algorithm, commonly utilised as a dynamic approach to improve the learning phase and convergence of the neural network. In this paper, a Hybrid Modified Lion Optimisation algorithm (LOA) with discrete Hopfield neural network (DHNN) is proposed for Boolean Satisfiability programming with different complexities. The powerful operators in LOA can be leveraged to reduce the computational burden in DHNN. The findings manifest the performance of the hybrid DHNN model in terms of sensitivity, accuracy, convergence rate, robustness, and computational time.
Keywords: Lion Optimization algorithm, discrete Hopfield neural network, Boolean Satisfiability