Simulated annealing heuristic for the general share-a-ride problem. Issue 7 (3rd July 2018)

• Record Type: Journal Article
• Authors: Yu, Vincent F.; Purwanti, Sesya Sri; Redi, A. A. N. Perwira; Lu, Chung-Cheng; Suprayogi, Suprayogi; Jewpanya, Parida
• Is Part Of: Engineering optimization. Volume 50:Issue 7(2018)
• Page Start: 1178
• Page End: 1197
• Publication Date: 2018-07-03
• Subjects: General share-a-ride problem -- ride sharing -- share-a-ride problem -- simulated annealing; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2018.1437153
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: This research introduces an extension of the share-a-ride problem (SARP), called the general share-a-ride problem (G-SARP). Similarly to SARP, a 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 of a passenger, and the number of parcel requests that can be inserted between the pick-up and drop-off points of a passenger is limited only by vehicle capacity. A 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.