Shuffled frog-leaping algorithm (SFLA) is a heuristic optimization technique based on swarm intelligence that is inspired by foraging behavior of the swarm of frogs. The traditional SFLA is easy to be premature convergence. So, we present an improved shuffled frog-leaping algorithm with single step search strategy and interactive learning rule(called ‘SI-SFLA’). Single step search strategy enha...

Stochastic search algorithms that take their inspiration from nature are gaining a great attention of many researchers to solve high dimension and non – linear complex optimization problems for which traditional methods fails. Shuffled frog – leaping algorithm (SFLA) is recent addition to the family of stochastic search algorithms that take its inspiration from the foraging process of frogs. SF...

The paper presents using Differential Evolution (DE) and Shuffled Frog Leaping Algorithm (SFLA) to optimally tune parameters of a fuzzy logic controller stabilizing a rotary inverted pendulum system at its upright equilibrium position. Both the DE and SFLA are meta-heuristic search methods. DE belongs to the class of evolutionary algorithms while SFLA is inspired from the memetic evolution of a...

This paper presents an effective shuffled frogleaping algorithm (SFLA) for solving a lot-streaming flow shop scheduling problem with equal-size sublots, where a criterion is to minimize maximum completion time (i.e., makespan) under both an idling and no-idling production cases. Unlike the original SFLA, the proposed SFLA represents an individual or frog as a job permutation and utilizes a posi...

This paper proposes Hybrid SFL-Bees Algorithm that combines strengths of Shuffled Frog Leaping Algorithm (SFLA) and Bees Algorithms (BA). While SFLA can find optimal solutions quickly because of directive searching and exchange of information, BA has higher random that make it easily escape local optima to find global solutions. Thus Hybrid SFL-Bees Algorithm is able to find optimal solutions q...

Reconfigurable system on chip is well known for its flexibility for high performance embedded systems. The hardware/software (HW/SW) partitioning is the most important phase during the design of reconfigurable system on chip. A great many different algorithms have been adopted for solving the hardware/software partitioning problem. Shuffled Frog Leaping Algorithm (SFLA) is popular for its simpl...

This paper proposes Hybrid SFL-Bees Algorithm that combines strengths of Shuffled Frog Leaping Algorithm (SFLA) and Bees Algorithms (BA). While SFLA can find optimal solutions quickly because of directive searching and exchange of information, BA has higher random that make it easily escape local optima to find global solutions. Thus Hybrid SFL-Bees Algorithm is able to find optimal solutions q...

This paper proposes a novel population-based evolution algorithm named grouping-shuffling particle swarm optimization (GSPSO) by hybridizing particle swarm optimization (PSO) and shuffled frog leaping algorithm (SFLA) for continuous optimization problems. In the proposed algorithm, each particle automatically and periodically executes grouping and shuffling operations in its flight learning evo...

In this paper, we propose a new gene selection algorithm based on Shuffled Frog Leaping Algorithm that is called SFLA-FS. The proposed algorithm is used for improving cancer classification accuracy. Most of the biological datasets such as cancer datasets have a large number of genes and few samples. However, most of these genes are not usable in some tasks for example in cancer classification. ...

This paper proposes a study of quality of service (QoS) in cognitive radio networks. This study is based on a stochastic optimization method called shuffled frog leaping algorithm (SFLA). The interest of the SFLA algorithm is to guarantee a better solution in a multi-carrier context in order to satisfy the requirements of the secondary user (SU).