Abstract
In urban areas, the cost of road congestion has paid great attention to the sociological, technological and environmental aspects, such as the optimal route and fuel consumption. This step is towards a smarter vehicle mobility where the travel time will be planned and dynamically adapted to changes with actual status of the traffic flow. In this article a multi-objective ACO algorithm is proposed to solve the daily carpooling problem. In particular, a set of decision variables are proposed in order to minimize three objective functions subject to a set of constraints on these objectives.
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