Genetic Algorithms and Ant Colony Approach for Gas-lift Allocation Optimization

Ant Colony Optimization Using Genetic Algorithms

A Genetic algorithms is a search technique used to find true or approximate solutions to optimization and search problems. Hybrid algorithms is proposed to solve combinatorial optimization problem by using "Ant colony and Genetic programming algorithms". The genetic programming paradigm permits the evolution of computer programs which can perform intermediate calculations, which can perform com...

Relationship between Genetic Algorithms and Ant Colony Optimization Algorithms

Genetic Algorithms (GAs) were introduced by Holland as a computational analogy of adaptive systems. GAs are search procedures based on the mechanics of natural selection and natural genetics. Ant Colony Optimization (ACO) is a metaheuristic inspired by the foraging behavior of ant colonies. ACO was introduced by Dorigo and has evolved significantly in the last few years. Both algorithms have sh...

Optimization of PID Controllers Using Ant Colony and Genetic Algorithms

New Approach for Solving Dynamic Travelling Salesman Problem with Hybrid Genetic Algorithms and Ant Colony Optimization

Dynamic travelling salesman problem (DTSP) is one of the optimization issues which it is not solvable with classical methods. To solve this problem, various solutions in the literature can be seen that each has advantages and disadvantages. Genetic Algorithm (GA) and Ant Colony Optimization (ACO) have been good to solve the DTSP. In this paper, we highlight a new algorithm by combining genetic ...

New Approach for Solving Dynamic Traveling Salesman Problem with Hybrid Genetic Algorithms and Ant Colony Optimization

Dynamic travelling salesman problem (DTSP) is one of the optimization issues which it is not solvable with classical methods. To solve this problem, various solutions in the literature can be seen that each has advantages and disadvantages. Genetic Algorithm (GA) and Ant Colony Optimization (ACO) have been good to solve the DTSP. In this paper, we highlight a new algorithm by combining genetic ...