Paper Info
Title
An adaptive large neighborhood search heuristic for the share-a-ride problem.
Abstract
The Share-a-Ride Problem (SARP) aims at maximizing the profit of serving a set of passengers and parcels using a set of homogeneous vehicles. We propose an adaptive large neighborhood search (ALNS) heuristic to address the SARP. Furthermore, we study the problem of determining the time slack in a SARP schedule. Our proposed solution approach is tested on three sets of realistic instances. The performance of our heuristic is benchmarked against a mixed integer programming (MIP) solver and the Dial-a-Ride Problem (DARP) test instances. Compared to the MIP solver, our heuristic is superior in both the solution times and the quality of the obtained solutions if the CPU time is limited. We also report new best results for two out of twenty benchmark DARP instances.
Year
DOI
Venue
2016
10.1016/j.cor.2015.08.008
Computers & Operations Research
Keywords
Field
DocType
Transportation,The Share-a-Ride Problem (SARP),Adaptive large neighborhood search,Slack time
Mathematical optimization,Central processing unit,Heuristic,Computer science,Homogeneous,Least slack time scheduling,Integer programming,Solver,Large neighborhood search
Journal
Volume
Issue
ISSN
66
C
0305-0548
Citations 
PageRank 
References 
9
0.54
26
Authors
4
Name
Order
Citations
PageRank
Baoxiang Li1261.75
Dmitry Krushinsky2455.04
eu354939.51
Hajo A. Reijers43424193.65