Here, a mixed-integer linear programming model is developed to represent a transportation system of students traveling from/to a university campus. The concept of ridesharing is used and the mechanism of combinatorial auctions is incorporated within a routing-based model. The mathematical model is based on the vehicle routing problem along with appropriate constraints accommodating features that express the auction clearing phase. A hybrid heuristic-based optimization framework, that takes advantage of meta-heuristic algorithms to improve an initial solution, is also developed to solve large-sized instances of the problem. Three meta-heuristics, namely particle swarm optimization, dragonfly algorithm, and imperialist competitive algorithm, are implemented in the proposed framework, whose performances are assessed and compared. Moreover, two improvement heuristic procedures that attempt to improve the outcomes of the foregoing meta-heuristics are proposed and compared as well.
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