Simulated annealing heuristic for the general share-a-ride problem

Vincent F. Yu, Sesya Sri Purwanti, A. A.N.Perwira Redi*, Chung-Cheng Lu, Suprayogi Suprayogi, Parida Jewpanya

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


This research introduces an extension of the share-a-ride problem (SARP), called the general share-a-ride problem (G-SARP). Similarly to SARP. taxi in G-SARP can service passenger and package requests at the same time. However, G-SARP allows the taxi to transport more than one passenger at the same time, which is more beneficial in practical situations. In addition, G-SARP has no restrictions on the maximum riding time o. passenger, and the number of parcel requests that can be inserted between the pick-up and drop-off points o. passenger is limited only by vehicle capacity. simulated annealing (SA) algorithm is proposed to solve G-SARP. The proposed SA algorithm is compared with basic SA and tabu search (TS) algorithms. The results show that the proposed SA algorithm outperforms basic SA and TS algorithms. Moreover, further analysis shows that G-SARP solutions are better than those of SARP in most cases.

Original languageEnglish
Pages (from-to)1178-1197
Number of pages20
JournalEngineering Optimization
Issue number7
StatePublished - 3 Jul 2018


  • General share-a-ride problem
  • ride sharing
  • share-a-ride problem
  • simulated annealing


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