Ride sharing with flexible participants: a metaheuristic approach for large‐scale problems

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Abstract
Severe traffic congestion and growing ecological consciousness have led to the rise of alternative transportation systems. Ride sharing is one such alternative in which drivers and passengers with similar time schedules and travel plans are matched. For this service to be effective, a large number of users are required to increase the probability of finding suitable travel partners. The present paper proposes a late acceptance metaheuristic to decide which users act as drivers and to construct their routes. The underlying optimization model allows passengers to walk to/from alternative pickup/drop‐off locations so as to further exploit user flexibility. A computational study quantifies the impact of different types of participant flexibility on CO2 emissions. These insights can inform and support policymakers in organizing effective ride‐sharing systems.

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