A novel framework of hyper-heuristic approach and its application in location-routing problem with simultaneous pickup and delivery

This paper addresses a new variant of location-routing problem (LRP), namely the LRP with simultaneous pickup and delivery (LRPSPD). A hyper-heuristic approach based on iterated local search (ILS-HH) is introduced to automatically optimize the LRPSPD. On basis of the novel proposed framework of hyper-heuristic, four selections mechanisms and five activation strategies are developed to examine the performance of the proposed framework. Three types computational evaluations were carried out and several conclusions can be drawn: (1) the proposed framework performs better than the classical one with performing several heavy-duty combinations of strategies in terms of solution quality and computing time; (2) different activated strategies have slight (not significant) effect on exploiting best solutions; (3) FRR-MAB-TS (fitness ratio rank based on multi-armed bandit with tabu search) works best among all selection methods. Moreover, the proposed approach could provide competitive, even better results compared to fine-tuned bespoke state-of-the-art approaches.