Abstract
The optimization problems usually need specific techniques to solve, therefore
many approaches and methods were proposed to solved such problems, but there are
many difficulties (limitations) still faced the problem solvers such as how to reach the
solution (or solutions) with high performance and efficiency or with more accuracy
results or with suitable behavior.
Thus the artificial intelligence tools are considered the best tools that can be used to
solve the optimization problems, because the AI tools must decide two important
aims: the problem reduction and the guarantee of solutions which lead to less the
effect of the difficulties (limitations) and give more suitable criteria in performance,
efficiency, and behavior. The swarm intelligent techniques are considered the most
modern AI techniques which contains many approaches that are used to solve
optimization problems with high performance and efficiency and suitable behavior
In this paper a specific study is made to the behavior of the swarm intelligence
techniques and evaluates its performance to solve various problems, then there is a
presentation to a scientific comparative section in which many approaches is
presented that used different swarm intelligence techniques such as Ant Colony
Optimization (ACO), Bees Algorithm (BA), and Particle Swarm Optimization (PSO)
to solve various optimization problems and them make a comparison among them in
term of behavior and performance. Finally we reach to scientific discussion and
conclusions that distinguish among the presented approaches to prove that the swarm
intelligence techniques success in solving practical, important, and applicable
problems with high performance, efficiency, and special behavior.
many approaches and methods were proposed to solved such problems, but there are
many difficulties (limitations) still faced the problem solvers such as how to reach the
solution (or solutions) with high performance and efficiency or with more accuracy
results or with suitable behavior.
Thus the artificial intelligence tools are considered the best tools that can be used to
solve the optimization problems, because the AI tools must decide two important
aims: the problem reduction and the guarantee of solutions which lead to less the
effect of the difficulties (limitations) and give more suitable criteria in performance,
efficiency, and behavior. The swarm intelligent techniques are considered the most
modern AI techniques which contains many approaches that are used to solve
optimization problems with high performance and efficiency and suitable behavior
In this paper a specific study is made to the behavior of the swarm intelligence
techniques and evaluates its performance to solve various problems, then there is a
presentation to a scientific comparative section in which many approaches is
presented that used different swarm intelligence techniques such as Ant Colony
Optimization (ACO), Bees Algorithm (BA), and Particle Swarm Optimization (PSO)
to solve various optimization problems and them make a comparison among them in
term of behavior and performance. Finally we reach to scientific discussion and
conclusions that distinguish among the presented approaches to prove that the swarm
intelligence techniques success in solving practical, important, and applicable
problems with high performance, efficiency, and special behavior.