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2. Ant colony optimization algorithms - Wikipedia

   en.wikipedia.org/wiki/Ant_colony_optimization...

   In the ant colony optimization algorithms, an artificial ant is a simple computational agent that searches for good solutions to a given optimization problem. To apply an ant colony algorithm, the optimization problem needs to be converted into the problem of finding the shortest path on a weighted graph. In the first step of each iteration ...

3. Humanoid ant algorithm - Wikipedia

   en.wikipedia.org/wiki/Humanoid_Ant_algorithm

   The humanoid ant algorithm (HUMANT) [1] is an ant colony optimization algorithm. The algorithm is based on a priori approach to multi-objective optimization (MOO), which means that it integrates decision-makers preferences into optimization process. [2] Using decision-makers preferences, it actually turns multi-objective problem into single ...

4. Evolutionary algorithm - Wikipedia

   en.wikipedia.org/wiki/Evolutionary_algorithm

   Ant colony optimization is based on the ideas of ant foraging by pheromone communication to form paths. Primarily suited for combinatorial optimization and graph problems. Particle swarm optimization is based on the ideas of animal flocking behaviour. Also primarily suited for numerical optimization problems.

5. Bacterial colony optimization - Wikipedia

   en.wikipedia.org/wiki/Bacterial_colony_optimization

   The bacterial colony optimization algorithm is an optimization algorithm which is based on a lifecycle model that simulates some typical behaviors of E. coli bacteria during their whole lifecycle, including chemotaxis, communication, elimination, reproduction, and migration. [1]

6. Genetic algorithm - Wikipedia

   en.wikipedia.org/wiki/Genetic_algorithm

   Ant colony optimization (ACO) uses many ants (or agents) equipped with a pheromone model to traverse the solution space and find locally productive areas. Although considered an Estimation of distribution algorithm , [ 64 ] Particle swarm optimization (PSO) is a computational method for multi-parameter optimization which also uses population ...

7. Evolutionary computation - Wikipedia

   en.wikipedia.org/wiki/Evolutionary_computation

   Evolutionary computation techniques can produce highly optimized solutions in a wide range of problem settings, making them popular in computer science. Many variants and extensions exist, suited to more specific families of problems and data structures.