Multi-modal multi-criteria personalized route planning by integrating AHP weighting method, quantifier-guided OWA operators and genetic algorithm

A multimodal multi-criteria route planning (MMRP) system provides an optimal multimodal route from an origin point to a destination point considering two or morecriteria in a way this route can be a combination of public and private transportation modes. In this research, analytical hierarchy process (AHP), quantifier-guided OWA operators and genetic algorithm (GA) have been used for MMRP. The main aspect of the quantifierguidedOWA is supporting different decision strategies. A decision strategy defines whether a user insists on satisfying all of his/her preferences regarding the selection of one route from a set of routes or he/she will be happy if most of criteria would be satisfied. In this study, five transportation modes, including subway, bus rapid transit (BRT), taxi, walking, and bus were considered for moving between nodes. Also, the fare, the time, theuser’s bother, and the length of the path were considered as effective criteria for solving the problem. The proposed models were implemented in an area in center of Tehran in a GUI MATLAB programming language. The results proved that, on average 80% of the userswith different decision strategies, selected the model’s proposed route as the best route.

Keywords:

Multi-modal multi criteria personalized route planning , Analytical Hierarchy Process (AHP) , quantifier-guided Ordered Weighted averaging (Q-OWA) operator , genetic algorithm (GA)