Search results
Results From The WOW.Com Content Network
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 ...
It is possible to adapt Dijkstra's algorithm to handle negative weights by combining it with the Bellman-Ford algorithm (to remove negative edges and detect negative cycles): Johnson's algorithm. The A* algorithm is a generalization of Dijkstra's algorithm that reduces the size of the subgraph that must be explored, if additional information is ...
ECJ is a freeware evolutionary computation research system written in Java. It is a framework that supports a variety of evolutionary computation techniques, such as genetic algorithms, genetic programming, evolution strategies, coevolution, particle swarm optimization, and differential evolution.
This is a chronological table of metaheuristic algorithms that only contains fundamental computational intelligence algorithms. Hybrid algorithms and multi-objective algorithms are not listed in the table below.
IMSL Numerical Libraries – linear, quadratic, nonlinear, and sparse QP and LP optimization algorithms implemented in standard programming languages C, Java, C# .NET, Fortran, and Python. IOSO – (Indirect optimization on the basis of Self-Organization) a multi-objective, multidimensional nonlinear optimization technology.
A minimum spanning tree of a weighted planar graph.Finding a minimum spanning tree is a common problem involving combinatorial optimization. Combinatorial optimization is a subfield of mathematical optimization that consists of finding an optimal object from a finite set of objects, [1] where the set of feasible solutions is discrete or can be reduced to a discrete set.
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
In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, tune, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem or a machine learning problem, especially with incomplete or imperfect information or limited computation capacity.