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- W2917261650 abstract "The transportation of elderly and impaired people is commonly solved as a Dial-A-Ride Problem (DARP). The DARP aims to design pick-up and delivery vehicle routing schedules. Its main objective is to accommodate as many users as possible with a minimum operation cost. It adds realistic precedence and transit time constraints on the pairing of vehicles and customers. This paper tackles the DARP with time windows (DARPTW) from a new and innovative angle as it combines hybridization techniques with an adaptive large neighborhood search heuristic algorithm. The main objective is to improve the overall real-life performance of vehicle routing operations. Real-life data are refined and fed to a hybrid adaptive large neighborhood search (Hybrid-ALNS) algorithm which provides a near-optimal routing solution. The computational results on real-life instances, in the Canadian city of Vancouver and its region, and DARPTW benchmark instances show the potential improvements achieved by the proposed heuristic and its adaptability." @default.
- W2917261650 created "2019-03-02" @default.
- W2917261650 creator A5073298343 @default.
- W2917261650 date "2019-02-16" @default.
- W2917261650 modified "2023-09-25" @default.
- W2917261650 title "A Hybrid Adaptive Large Neighborhood Heuristic for a Real-Life Dial-a-Ride Problem" @default.
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- W2917261650 doi "https://doi.org/10.3390/a12020039" @default.
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