Publication Type
Journal Article
Version
acceptedVersion
Publication Date
5-2024
Abstract
The home-refill delivery system is a business model that addresses the concerns of plastic waste and its impact on the environment. It allows customers to pick up their household goods at their doorsteps and refill them into their own containers. However, the difficulty in accessing customers’ locations and product consolidations are undeniable challenges. To overcome these issues, we introduce a new variant of the Profitable Tour Problem, named the multi-vehicle profitable tour problem with flexible compartments and mandatory customers (MVPTPFC-MC). The objective is to maximize the difference between the total collected profit and the traveling cost. We model the proposed problem as Mixed Integer Linear Programming and present an Adaptive Large Neighborhood Search (ALNS) algorithm to solve it. Our ALNS outperforms the commercial solver, Gurobi, and Large Neighborhood Search (LNS), as proven by giving better solutions within reasonable computational times. Both ALNS and LNS can obtain optimal solutions for all small instances and three better solutions than Gurobi for medium problems. Furthermore, ALNS is also robust and effective in solving large MVPTPFC-MC, as proven by resulting in better solutions within less CPU time than LNS. Finally, more analyses are conducted to justify the utilization of flexible compartment sizes by comparing it with fixed compartment sizes and to evaluate the robustness of MVPTPFC-MC. The results show that utilizing flexible compartment sizes can yield more benefits than fixed compartment sizes, particularly when the fleet size is limited, and there are fewer mandatory customers to serve.
Keywords
Flexible compartment, Home-refill, Mandatory customer, Multi-compartment, Multi-trip
Discipline
Numerical Analysis and Scientific Computing | Operations Research, Systems Engineering and Industrial Engineering | Theory and Algorithms
Research Areas
Intelligent Systems and Optimization
Publication
Applied Soft Computing
Volume
156
First Page
1
Last Page
17
ISSN
1568-4946
Identifier
10.1016/j.asoc.2024.111482
Publisher
Elsevier
Citation
YU, Vincent F.; SALSABILA, Nabila Yuraisyah; GUNAWAN, Aldy; and HANDOKO, Anggun Nurfitriani.
An adaptive large neighborhood search for the multi-vehicle profitable tour problem with flexible compartments and mandatory customers. (2024). Applied Soft Computing. 156, 1-17.
Available at: https://ink.library.smu.edu.sg/sis_research/8713
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1016/j.asoc.2024.111482
Included in
Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Theory and Algorithms Commons