Multi-atomic Annealing Heuristic for Static Dial-a-ride Problem

June 29, 2018 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Song Guang Ho, Ramesh Ramasamy Pandi, Sarat Chandra Nagavarapu, Justin Dauwels arXiv ID 1807.02406 Category cs.AI: Artificial Intelligence Citations 1 Venue arXiv.org Last Checked 4 months ago
Abstract
Dial-a-ride problem (DARP) deals with the transportation of users between pickup and drop-off locations associated with specified time windows. This paper proposes a novel algorithm called multi-atomic annealing (MATA) to solve static dial-a-ride problem. Two new local search operators (burn and reform), a new construction heuristic and two request sequencing mechanisms (Sorted List and Random List) are developed. Computational experiments conducted on various standard DARP test instances prove that MATA is an expeditious meta-heuristic in contrast to other existing methods. In all experiments, MATA demonstrates the capability to obtain high quality solutions, faster convergence, and quicker attainment of a first feasible solution. It is observed that MATA attains a first feasible solution 29.8 to 65.1% faster, and obtains a final solution that is 3.9 to 5.2% better, when compared to other algorithms within 60 sec.
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