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Pheromone trail optimization

Swarm intelligence is a term that is applied to two rather different techniques — ant colony or pheromone trail optimization and particle swarm optimization. We deal here briefly with the latter. [Pg.166]

Recent methods draw on natural mimicry to find best solutions by using swarms of either pseudo-ants or -bees to test a large number of possible alternatives to find the ones that work well. Ant colony methods are useful in other fields such as delivery route optimization (the traveling salesman problem), but in essence the natural systems are individually trying many options in parallel and reporting back to the other members of the colony about the success or otherwise of their attempts. In the natural world, this is encoded by a pheromone trail and in the computational world it is the upweighting of selection parameters [62,63]. [Pg.444]

The ant algorithm reproduces this behaviour of ant colonies in the pheromone trail update procedure. The search for a solution is terminated, when the maximum number of iterations has been reached or the maximum computational time has been achieved. Then, the shortest trajectoiy is selected from all of the solutions found by the artificial ants. Afterwards, the best solution is presented in a graphical form and the new course of the own ship at every segment of the determined safe, optimal trajectory is displayed. If the algorithm has not found a solution, such information is displayed after the calculations are completed. The flowchart of the ant algorithm for safe ship trajectoiy planning is shown in Figure 1. [Pg.154]

The fact that mating disruption can be commercially feasible is encouraging but the actual mechanism(s) of disruption is still unclear. The possible mechanisms involved in disruption include sensory adaptation, habituation, competition ("false-trail following") and camouflage of aerial trails from females (14, 15). These mechansims could be working in combination, simultaneously or sequentially, so that some level of disruption can and does occur under a variety of conditions. Without a better understanding of the mechanisms of "attraction" to a pheromone source and the mating disruption process, however, optimization of control methods can proceed only on an empirical basis. [Pg.38]

An optimal group in which to examine trail pheromone evolution is the garter snakes of the Thamnophis radix complex. In the United States, this complex consists of six recently evolved but distinct species radix,... [Pg.273]


See other pages where Pheromone trail optimization is mentioned: [Pg.164]    [Pg.165]    [Pg.174]    [Pg.167]   
See also in sourсe #XX -- [ Pg.166 , Pg.170 ]




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