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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 ...
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 ...
Reactive search optimization focuses on combining machine learning with optimization, by adding an internal feedback loop to self-tune the free parameters of an algorithm to the characteristics of the problem, of the instance, and of the local situation around the current solution. Genetic algorithms maintain a pool of solutions rather than ...
The ant colony optimization algorithm is a probabilistic technique for solving computational problems that can be reduced to finding good paths through graphs.Initially proposed by Marco Dorigo in 1992 in his PhD thesis, [1] [2] the first algorithm aimed to search for an optimal path in a graph based on the behavior of ants seeking a path between their colony and a source of food.
Tabu search is often benchmarked against other metaheuristic methods — such as simulated annealing, genetic algorithms, ant colony optimization algorithms, reactive search optimization, guided local search, or greedy randomized adaptive search. In addition, tabu search is sometimes combined with other metaheuristics to create hybrid methods.
Ant colony optimization (ACO), introduced by Dorigo in his doctoral dissertation, is a class of optimization algorithms modeled on the actions of an ant colony. ACO is a probabilistic technique useful in problems that deal with finding better paths through graphs.
3.1 Pseudocode. 4 Related methods. ... The same CE algorithm can be used for optimization, rather than estimation. ... Ant colony optimization algorithms; See also
Bacterial colony optimization; Barzilai-Borwein method; Basin-hopping; Benson's algorithm; Berndt–Hall–Hall–Hausman algorithm; Bin covering problem; Bin packing problem; Bland's rule; Branch and bound; Branch and cut; Branch and price; Bregman Lagrangian; Bregman method; Broyden–Fletcher–Goldfarb–Shanno algorithm