The inability of conventional energy sources to fully meet the rapidly increasing energy demands in today’s world has led to the growing importance of hybrid power generation systems that incorporate renewable energy sources. This work proposes an optimally designed multi-source standalone hybrid generation system comprising of photovoltaic panels, wind turbine generators, batteries and diesel ...

Abstract Multi-objective particle swarm optimization algorithms encounter significant challenges when tackling many-objective problems. This is mainly because of the imbalance between convergence and diversity that occurs increasing selection pressure. In this paper, a novel adaptive MOPSO (ANMPSO) algorithm based on R2 contribution method developed to improve performance MOPSO. First, new glob...

the dogleg severity is one of the most important parameters in directional drilling. improvement of these indicators actually means choosing the best conditions for the directional drilling in order to reach the target point. selection of high levels of the dogleg severity actually means minimizing well trajectory, but on the other hand, increases fatigue in drill string, increases torque and d...

in this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classifypatterns of different classes in the feature space. the introduced mutation operators and chaotic sequences allows us to overcomethe problem of early convergence into a local minima associated with particle swarm optimization algorithms. that is, the mutationope...

Currently, the researchers have made a lot of hybrid particle swarm algorithm in order to solve the shortcomings that the Particle Swarm Algorithms is easy to converge to local extremum, these algorithms declare that there has been better than the standard particle swarm. This study selects three kinds of representative hybrid particle swarm optimizations (differential evolution particle swarm ...

The objective of this thesis is to investigate how to improve Particle Swarm Optimization by hybridization of stochastic search heuristics and by a Self-Organized Criticality extension. The thesis will describe two hybrid models extending Particle Swarm Optimization with two aspects from Evolutionary Algorithms, recombination via breeding and gene flow restriction via subpopulations. A further ...

The main objective of this study is to reduce optimal vibration suppression of Timoshenko beam under non-periodic step and impulse inputs. Cantilever beam was modeled by Timoshenko theory and finite element numerical method. Stiffness (K), mass (M), and damping (C) matrices are extracted. Then, in order to control structure vibration, piezoelectric patches were used due to simultaneous dual beh...

This paper presents a novel scheduling of resource-constrained Flexible Manufacturing System (FMS) with consideration the following sub-problems: (i) machine loading and unloading, (ii) manufacturing operation scheduling, (iii) assignment, (iv) Automated Guided Vehicle (AGV) scheduling. In proposed model, both AGV machinery are considered as required resources. Energy efficiency AGVs has been s...

Shared manufacturing is recognized as a new point-to-point mode in the digital era. referred to realize dynamic allocation of tasks and resources. Compared with traditional mode, shared offers more abundant resources flexible configuration options. This paper proposes model based on description environment, characteristics resource allocation. The execution tasks, which candidate enter or exit ...

This paper presents the application of two swarm intelligence techniques, multi-objective artificial bee colony (MOABC) and particle optimization (MOPSO), to optimal design a complementary metal oxide semiconductor (CMOS) low noise amplifier (LNA) cascode with inductive source degeneration. The aim is achieve balanced trade-off between voltage gain figure. optimized LNA circuit operates at 2.4 ...