Abstract
For obvious practical reasons, NP-complete problems are typically solved by applying heuristic methods. In this regard, nature has inspired many heuristic algorithms to obtain reasonable solutions to complex problems. One of these algorithms is River Formation Dynamics (RFD). This heuristic optimization method is based on imitating how water forms rivers by eroding the ground and depositing sediments. After drops transform the landscape by increasing/decreasing the altitude of places, solutions are given in the form of paths of decreasing altitudes. Decreasing gradients are constructed, and these gradients are followed by subsequent drops to compose new gradients and reinforce the best ones. In this chapter, we apply RFD to solve three NP-complete problems, and we compare our results with those obtained by using Ant Colony Optimization (ACO).KeywordsShort PathDestination NodeMinimum Span TreeTravel Salesman ProblemTravel Salesman ProblemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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