Abstract
This study develops a model for customer selection and vehicle scheduling with time windows for moving companies. To reflect the actual operations of moving companies, the proposed model employs two major processes to extend the traditional vehicle routing models. First, loading and unloading activities of moving vehicles are explicitly modeled using the technique of time–space networks. Second, moving companies are flexible in selecting customers, thereby possibly maximizing the profit of companies. The model is formulated as an integer multi-commodity network with side constraints. A decomposition-based solution algorithm is developed to solve the problem efficiently. Results of a case study indicate that the proposed methodology efficiently generates reasonable plans of customer selection and vehicle scheduling. Sensitivity analysis shows that the proposed model properly responds to the change in critical parameters. Therefore, the proposed methodology has a strong potential to improve the operations and profitability of moving companies.
Original language | English |
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Pages (from-to) | 613-622 |
Number of pages | 10 |
Journal | Transportation Letters |
Volume | 12 |
Issue number | 9 |
DOIs | |
State | Published - 20 Oct 2020 |
Keywords
- Moving company
- multi-commodity network flow model
- solution algorithm
- time–space network