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A honeybee mating optimization algorithm for solving the static bike rebalancing problem

Published: 13 July 2019 Publication History

Abstract

This paper proposes a new approach to solve the Bike Rebalancing Problem (BRP) based on the Honey-Bee Mating Optimization (HBMO) algorithm. The aim is to reduce the overall traveling cost of redistribution operations under various constraints. The performance of the proposed algorithm is evaluated using a set of benchmark instances for the BRP. Preliminary results are obtained and showed that the proposed approach is promising.

References

[1]
Hussein A Abbass. 2001a. A monogenous MBO approach to satisfiability. In Proceeding of the international conference on computational intelligence for modelling, control and automation, CPMCA.
[2]
Hussein A Abbass. 2001b. MBO: Marriage in honey bees optimization-A haplometrosis polygynous swarming approach. In Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No. 01TH8546), Vol. 1. IEEE, 207--214.
[3]
Mauro Dell'Amico, Eleni Hadjicostantinou, Manuel Iori, and Stefano Novellani. 2014. The bike sharing rebalancing problem: Mathematical formulations and benchmark instances. Omega 45 (2014), 7--19.
[4]
Ahmed Abdelmoumene Kadri, Imed Kacem, and Karim Labadi. 2016. A branch-and-bound algorithm for solving the static rebalancing problem in bicycle-sharing systems. Computers & Industrial Engineering 95 (2016), 41--52.
[5]
Christian Prins. 2004. A simple and effective evolutionary algorithm for the vehicle routing problem. Computers & Operations Research 31, 12 (2004), 1985--2002.

Cited By

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  • (2022)Mobility prediction for uneven distribution of bikes in bike sharing systemsConcurrency and Computation: Practice and Experience10.1002/cpe.746535:2Online publication date: 3-Nov-2022

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cover image ACM Conferences
GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion
July 2019
2161 pages
ISBN:9781450367486
DOI:10.1145/3319619
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 July 2019

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Author Tags

  1. bike rebalancing problem
  2. heuristics
  3. honey bee mating optimization
  4. vehicle routing problem

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GECCO '19
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GECCO '19: Genetic and Evolutionary Computation Conference
July 13 - 17, 2019
Prague, Czech Republic

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

View all
  • (2022)Mobility prediction for uneven distribution of bikes in bike sharing systemsConcurrency and Computation: Practice and Experience10.1002/cpe.746535:2Online publication date: 3-Nov-2022

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