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

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Abstract

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.

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Acknowledgements

Authors thank Professor Yu. V.F. and Lin. S.Y. for providing assistance during the experiment, and anonymous referees and editors for their constructive comments, time and patience devoted to the review of this paper. The presented research was supported by the National Natural Science Foundation of China (No. 61572438, 61873240, 61402409), Science Technology plan project of Zhejiang (No. 2017C33224) and National Natural Science Foundation of Zhejiang (No. Y19F030052).

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Authors and Affiliations

  1. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, 310012, Zhejiang, People’s Republic of China

    Yanwei Zhao, Longlong Leng & Chunmiao Zhang

  2. Jiaxing Vocational and Technical College, Jiaxing, 314036, Zhejiang, People’s Republic of China

    Chunmiao Zhang

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  1. Yanwei Zhao
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Correspondence to Yanwei Zhao.

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Appendix 1

Appendix 1

Table of acronyms

A

 AM

All moves

 Avg.

Average

B

 BC

Brand-and-cut

 BKS

Best known solution

C

 CS

Selection of HC

E

 ELS

Evolutionary local search

 FLP

Facility location problem

 FRR-MAB

Fitness ratio rank based on multi-armed bandit

 FRR-MAB-TS

FRR-MAB combined with TS

G

 GA

Genetic algorithm

 GD

Great deluge

 GH

Greedy heuristic

H

 HC

Hill climber

 HH

Hyper-heuristic

 HLH

High-level heuristic

I

 IE

Improving and equal

 ILS

Iterated local search

L

 LLH

Low-level heuristic

 LRP

Location-routing problem

 LRPSPD

LRP with simultaneous pickup and delivery

M

 MC

Monte Carlo

 MDVRP

Multi-depot vehicle routing problem

 MH

Mutational heuristic

 MS

Selection of MH

O

 OI

Only improving

R

 RD

Random descend

 RKGH

Regret-k greedy heuristic

 RP

Random permutation

S

 SA

Simulated annealing

 SR

Simple random

T

 TS

Tabu search

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Zhao, Y., Leng, L. & Zhang, C. A novel framework of hyper-heuristic approach and its application in location-routing problem with simultaneous pickup and delivery. Oper Res Int J 21, 1299–1332 (2021). https://doi.org/10.1007/s12351-019-00480-6

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