People and goods are transported independently in city logistics. New approaches to city logistics are needed to ensure efficient urban mobility for both people and goods. To solve this issue, the share-a-ride problem was developed, in which the same taxi network managed both people and goods in a coordinated way. This system can reduce pollution and urban congestion from a city perspective. The parcel delivery service offers new advantages from the perspective of a taxi company. This research introduces the share-a-ride problem with transfers (SARP-T), which is an extension of the share-a-ride problem (SARP) that allows passengers and parcels to transfer from one taxi to another at the transfer nodes. The goal of the share-a-ride problem with transfers (SARP-T) is to maximize the profit from serving parcel and passenger requests with taxis that depart from a depot. We developed a mixed integer linear program for SARP-T and proposed the simulated annealing with mutation strategy (SAMS) algorithm to solve the problem. Computational findings indicate that for small SARP-T benchmark instances, both the commercial solver CPLEX and our proposed SAMS algorithm attain optimal solutions. Furthermore, for large SARP-T benchmark instances, comparison results demonstrate that the proposed SAMS algorithm achieves better solution values than the basic SA heuristic. Our analysis also shows that SARP-T solutions are better than the share-a-ride problem (SARP), the general share-a-ride problem (G-SARP), and the share-a-ride problem with flexible compartments (SARPFC) solutions.

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