Stochastic Multi-Objective Multi-Trip AMR Routing Problem with Time Windows

Lulu Cheng, Ning Zhao and Kan Wu ()
Additional contact information
Lulu Cheng: Faculty of Science, Kunming University of Science and Technology, Kunming 650500, China
Ning Zhao: Faculty of Science, Kunming University of Science and Technology, Kunming 650500, China
Kan Wu: Business Analytics Research Center, Chang Gung University, Taoyuan City 33302, Taiwan

Mathematics, 2024, vol. 12, issue 15, 1-20

Abstract: In recent years, with the rapidly aging population, alleviating the pressure on medical staff has become a critical issue. To improve the work efficiency of medical staff and reduce the risk of infection, we consider the multi-trip autonomous mobile robot (AMR) routing problem in a stochastic environment. Our goal is to minimize the total expected operating cost and maximize the total service quality for patients, ensuring that each route violates the vehicle capacity and the time window with only a minimal probability. The travel time of AMRs is stochastically affected by the surrounding environment; the demand for each ward is unknown until the AMR reaches the ward, and the service time is linearly related to the actual demand. We developed a population-based tabu search algorithm (PTS) that combines the genetic algorithm with the tabu search algorithm to solve this problem. Extensive numerical experiments were conducted on the modified Solomon instances to demonstrate the efficiency of the PTS algorithm and reveal the impacts of the confidence level on the optimal solution, providing insights for decision-makers to devise delivery schemes that balance operating costs with patient satisfaction.

Keywords: autonomous mobile robot; scheduling; stochastic programming model; genetic algorithm; tabu search (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/12/15/2394/pdf (application/pdf)
https://www.mdpi.com/2227-7390/12/15/2394/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:12:y:2024:i:15:p:2394-:d:1447286

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().