Related papers: Application of PSO, Artificial Bee Colony and Bact…
This paper introduces a new optimisation algorithm, called Adaptive Bacterial Colony Optimisation (ABCO), modelled after the foraging behaviour of E. coli bacteria. The algorithm follows three stages--explore, exploit and reproduce--and is…
Metaheuristic particle swarm optimization (PSO) algorithm has emerged as one of the most promising optimization techniques in solving highly constrained non-linear and non-convex optimization problems in different areas of electrical…
A new approach to the solution of Economic Dispatch using Particle Swarm Optimization is presented. It is the progression of allocating production amongst the dedicated units such that the restriction forced are fulfilled and the power…
A wide range of engineering design problems have been solved by the algorithms that simulates collective intelligence in swarms of birds or insects. The Artificial Bee Colony or ABC is one of the recent additions to the class of swarm…
The Artificial Bee Colony (ABC) algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees' food search behavior. Since the ABC algorithm has been developed to achieve optimal solutions by…
The economic dispatch of generators is a major concern in thermal power plants that governs the share of each generating unit with an objective of minimizing fuel cost by fulfilling load demand. This problem is not as simple as it looks…
Economic Load Dispatch depicts a fundamental role in the operation of power systems, as it decreases the environmental load, minimizes the operating cost, and preserves energy resources. The optimal solution to Economic Load Dispatch…
A new adopted evolutionary algorithm is presented in this paper to solve the non-smooth, non-convex and non-linear multi-area economic dispatch (MAED). MAED includes some areas which contains its own power generation and loads. By…
Due to the rapid increase of air cargo and postal transport volume, an efficient automated multi-dimensional warehouse with elevating transfer vehicles (ETVs) should be established and an effective scheduling strategy should be designed for…
Particle swarm optimization (PSO) is attracting an ever-growing attention and more than ever it has found many application areas for many challenging optimization problems. It is, however, a known fact that PSO has a severe drawback in the…
Now the Meta-Heuristic algorithms have been used vastly in solving the problem of continuous optimization. In this paper the Artificial Bee Colony (ABC) algorithm and the Firefly Algorithm (FA) are valuated. And for presenting the…
In many technical fields, single-objective optimization procedures in continuous domains involve expensive numerical simulations. In this context, an improvement of the Artificial Bee Colony (ABC) algorithm, called the Artificial super-Bee…
We apply two evolutionary search algorithms: Particle Swarm Optimization (PSO) and Genetic Algorithms (GAs) to the design of Cellular Automata (CA) that can perform computational tasks requiring global coordination. In particular, we…
In this paper, we present a hybrid of Evolutionary Programming (EP) and Particle Swarm Optimization (PSO) algorithms for numerically efficient global optimization of antenna arrays and metasurfaces. The hybrid EP-PSO algorithm uses an…
Artificial bee colony (ABC) algorithm has proved its importance in solving a number of problems including engineering optimization problems. ABC algorithm is one of the most popular and youngest member of the family of population based…
One of the important issues in computer networks is "Load Balancing" which leads to efficient use of the network resources. To achieve a balanced network it is necessary to find different routes between the source and destination. In the…
As an effective algorithm for solving complex optimization problems, artificial bee colony (ABC) algorithm has shown to be competitive, but the same as other population-based algorithms, it is poor at balancing the abilities of global…
Non-polynomial hard (NP-hard) problems are challenging because no polynomial-time algorithm has yet been discovered to solve them in polynomial time. The Bacteria Foraging Optimization (BFO) algorithm is one of the metaheuristics algorithms…
An automated sizing approach for analog circuits using evolutionary algorithms is presented in this paper. A targeted search of the search space has been implemented using a particle generation function and a repair-bounds function that has…
Particle Swarm Optimization (PSO) is an Evolutionary Algorithm (EA) that utilizes a swarm of particles to solve an optimization problem. Slow Intelligence System (SIS) is a learning framework which slowly learns the solution to a problem…