oil production optimization is one of the main targets of reservoir management. smart well technology gives the ability of real time oil production optimization. although this technology has many advantages; optimum adjustment or sizing of corresponding valves is still an issue to be solved. in this research, optimum port sizing of inflow control devices (icds) which are passive control valves ...

A first investigation of the recently proposed Unified Particle Swarm Optimization algorithm on dynamic environments is provided and discussed on widely used test problems. Results are very promising compared to the corresponding results of the standard Particle Swarm Optimization algorithm, indicating the superiority of the new scheme.

In this paper, application of particle swarm algorithm in positioning and optimization of traffic in NoSQL database is discussed. Sample system is modeled with independent 2-order hyper exponential input stream of packets and exponential service time distribution. Optimization is solved using particle swarm algorithm for various scenarios of operation.

This paper try to solve the route optimization of stacker in automated storage and retrieval system with the hybrid algorithm which based on the combination of genetic algorithm and particle swarm optimization. First the algorithm generates the initial population by using particle swarm algorithm. And then the population undertakes assorted crossover and mutation in the iterative process by usi...

The main purpose of this paper is to solve an inverse random differential equation problem using evolutionary algorithms. Particle Swarm Algorithm and Genetic Algorithm are two algorithms that are used in this paper. In this paper, we solve the inverse problem by solving the inverse random differential equation using Crank-Nicholson's method. Then, using the particle swarm optimization algorith...

In recent years, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are time-varying. In this paper, a triggered memory scheme is introduced into the particle swarm optimization to deal with dynamic environments. The triggered memory scheme enhances traditional memory scheme with a trigger...