Dynamic path optimization algorithm based on spatial-temporal and genetic factor

Abstract

Dynamic path optimization method has long been regarded as one of the toughest yet pervasive problems in urban computing. The conjunct effects of spatial-temporal and genetic factor in path optimization are with few researches. To meet this critical challenge, in this paper, we pay a systematic study on the different classifier performance in class overlapping problem and propose a new dynamic path optimization method based on spatial-temporal and genetic factor. The algorithm keeps the neighborhood in traditional tabu algorithm, ensure strong climbing ability and go to the local optimization. At the same time, introduce the spatial-temporal and genetic factor to develop new search space for bounded domain considering spatial-temporal. Experimental results on selected data sets prove that dynamic path optimization algorithm based on spatial-temporal and genetic factor can have good performance for dynamic path optimization problem.