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 ...

Based on introducing two optimization algorithms, group search optimization (GSO) algorithm and particle swarm optimization (PSO) algorithm, a new hybrid optimization algorithm which named particle swarm-group search optimization (PS-GSO) algorithm is presented and its application to optimal structural design is analyzed. The PS-GSO is used to investigate the spatial truss structures with discr...

Particle swarm optimization (PSO) has shown to be an efficient, robust and simple optimization algorithm. Most of the PSO studies are empirical, with only a few theoretical analyses that concentrate on understanding particle trajectories. This paper overviews current theoretical studies, and extend these studies to applications in mechatronic systems, such as identification, control gains and o...

Particle swarm optimization (PSO) is an artificial intelligence (AI) technique that can be used to find approximate solutions to extremely difficult or impossible numeric maximization and minimization problems. Particle swarm optimization is an optimization method. It is an optimization algorithm, which is based on swarm intelligence. Optimization problems are widely used in different fields of...

Mathematical programming and artificial intelligence (AI) methods are known as the most effective and applicable procedures to form manufacturing cells in designing a cellular manufacturing system (CMS). In this paper, a bi-objective programming model is presented to consider the cell formation problem that is solved by a proposed multi-objective particle swarm optimization (MOPSO). The model c...

In recent days, Swarm Intelligence plays an important role in solving many real life optimization problems. Particle Swarm Optimization (PSO) is swarm intelligence based search and optimization algorithm which is used to solve global optimization problems. But due to lack of population diversity and premature convergence it is often trapped into local optima. We can increase diversity and preve...

-Particle Swarm Optimization (PSO) has received increased attention in the evolutionary computation fields recently. In the paper, we proposed Adaptive constriction factor for Location-related Particle Swarm (ALPS) that is shown to be superior when compared with the existing PSO algorithm. We adapt a technique of overcoming complex problems with PSO. This is accomplished by using the ratio of t...

This paper presents a new Artificial Bee Colony (ABC) optimization algorithm to solve function optimization problems. The proposed approach is called OCABC, which introduces opposition-based learning concept and dynamic Cauchy mutation into the standard ABC algorithm. To verify the performance of OCABC, eight well-known benchmark function optimization problems are used in the experiments. Exper...

In order to have clarity in the satellite images we have used Particle Swarm Optimization technique. When incorporated with traditional clustering algorithms, problems such as local optima and sensitivity to initialization, are reduced, thus exploring a greater area using global search. This segmented image is further classified using Kappa coefficient. Keywords— Particle Swarm Optimization(PSO...