Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows
New ideas in optimization
On how pachycondyla apicalis ants suggest a new search algorithm
Future Generation Computer Systems
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
The Ant Colony Metaphor for Searching Continuous Design Spaces
Selected Papers from AISB Workshop on Evolutionary Computing
Ant Colony Optimization
Continuous interacting ant colony algorithm based on dense heterarchy
Future Generation Computer Systems - Special issue: Computational chemistry and molecular dynamics
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
The hyper-cube framework for ant colony optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Expert Systems with Applications: An International Journal
Extended ant colony optimization for non-convex mixed integer nonlinear programming
Computers and Operations Research
Robot routing in sparse wireless sensor networks with continuous ant colony optimization
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
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The Ant Colony Optimization has gained great success in applications to combinatorial optimization problems, but few of them are proposed in the continuous domain. This paper proposes an ant algorithm, called Direct Ant Colony Optimization (DACO), for the function optimization problem in continuous domain. In DACO, artificial ants generate solutions according to a set of normal distribution, of which the characteristics are represented by pheromone modified by ants according to the previous search experience. Experimental results show the advantage of DACO over other ACO based algorithms for the function optimization problems of different characteristics.