AIJun 29, 2018

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

arXiv:1807.02406v1
AI Analysis

This addresses transportation scheduling with time windows, offering incremental improvements in solution quality and speed for logistics and routing applications.

The paper tackles the static dial-a-ride problem by proposing a multi-atomic annealing algorithm, which achieves a 3.9 to 5.2% better final solution and finds a first feasible solution 29.8 to 65.1% faster compared to other algorithms.

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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