An improved particle swarm optimizer (IPSO) with artificial immune algorithm (AIA) is proposed based on basic particle swarm optimization (BPSO). IPSO which is divided into two phases during the evolutionary process is different from BPSO. AIA remaining the diversity of population is applied in the first phase. Sub-population is formed by the optimum values sorted near the top from the first ph...

The asymmetric simple exclusion process (ASEP) with periodic boundary conditions is investigated for shuffled dynamics. In this type of update, in each discrete timestep the particles are updated in a random sequence. Such an update is important for several applications, e.g. for certain models of pedestrian flow in two dimensions. For the ASEP with shuffled dynamics and a related truncated pro...

To overcome the shortcomings of standard particle swarm optimization algorithm (PSO), such as premature convergence and low precision, a dynamic multi-swarm PSO with global detection mechanism (DMS-PSO-GD) is proposed. In DMS-PSO-GD, whole population divided into two kinds sub-swarms: several same-sized sub-swarms sub-swarm. The achieve information interaction sharing among themselves through r...

0-1 knapsack problem is a typical NP complete problem. Shuffled frog leaping algorithm is applied successfully in many combinational optimization problems. Therefore, the paper introduces an improved shuffled frog leaping algorithm for solving 0-1 knapsack problem. It greatly reduces the searching time of shuffled frog leaping algorithm. It also effectively ameliorates the disadvantage of easil...

This study investigates a hybrid algorithm between Grey Wolf Optimization (GWO) and Cuckoo Search (CS) algorithms to find the parameters of induction motors. The motor have been estimated by using data supplied manufacturer. problem for parameter estimation is formulated as an optimization problem. Then, solved GWO based on CS parameters. Numerical results show that both are capable solving fin...

DNA microarrays have been applied successfully in diverse research fields such as gene discovery, disease diagnosis and drug discovery. The roles of the genes and the mechanisms of the underlying diseases can be identified using microarrays. Biclustering is a two dimensional clustering problem, where we group the genes and samples simultaneously. It has a great potential in detecting marker gen...

In this work, we study task partitioning in the context of swarm robotics. Task partitioning refers to the decomposition of a task into sub-tasks that can be tackled by different workers. In this work, we focus on the case in which a task is partitioned into a sequence of sub-tasks that must be executed in a certain order. This implies that the sub-tasks must interface with each other, and that...

To overcome the challenges of Data gathering and enhancement of lifetime of mobile nodes we propose a new data gathering technique with multiple mobile sinks based on particle swarm optimization (PSO) technique. Particle changes its condition according to the following three principles in the basic particle swarm optimization algorithm: (1) to keep its inertia (2) to change the condition accord...