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Full-Text Articles in Engineering
Wolf Ant, Gilbert L. Peterson, Christopher M. Mayer, Kevin Cousin
Wolf Ant, Gilbert L. Peterson, Christopher M. Mayer, Kevin Cousin
Faculty Publications
Ant colony optimization (ACO) algorithms can generate quality solutions to combinatorial optimization problems. However, like many stochastic algorithms, the quality of solutions worsen as problem sizes grow. In an effort to increase performance, we added the variable step size off-policy hill-climbing algorithm called PDWoLF (Policy Dynamics Win or Learn Fast) to several ant colony algorithms: Ant System, Ant Colony System, Elitist-Ant System, Rank-based Ant System, and Max-Min Ant System. Easily integrated into each ACO algorithm, the PDWoLF component maintains a set of policies separate from the ant colony's pheromone. Similar to pheromone but with different update rules, the PDWoLF policies …
Network Formation Using Ant Colony Optimization -- A Systematic Review, Steven C. Oimoen, Gilbert L. Peterson, Kenneth M. Hopkinson
Network Formation Using Ant Colony Optimization -- A Systematic Review, Steven C. Oimoen, Gilbert L. Peterson, Kenneth M. Hopkinson
Faculty Publications
A significant area of research in the field of hybrid communications is the Network Design Problem (NDP) [1]. The NDP is an NP complete problem [1] that focuses on identifying the optimal network topology for transmitting commodities between nodes, under constraints such as bandwidth, limited compatible directed channels, and link and commodity costs. The NDP focuses on designing a flexible network while trying to achieve optimal flow or routing. If a link (or arc) is used, then an associated fixed cost of the edge is incurred. In addition, there is a cost for using the arc depending on the flow. …