The time-dependent multi-depot fleet size and mix green vehicle routing problem: improved adaptive large neighbourhood search

Abstract

This study presents a mathematical model for the multi-depot Time-Dependent Fleet Size and Mix Green Vehicle Routing Problem (TD-FSMGVRP). The objective function of the developed model is to minimize the total cost including vehicles’ fixed cost, drivers’ cost, fuel costs, and costs of Greenhouse Gas (GHG) emission. Fleet composition, load, vehicle speed, road slope, and traffic are considered as factors affecting the produced pollution. Considering the NP-Hard complexity of this problem, an Improved Adaptive Large Neighbourhood Search (IALNS) algorithm is designed to treat the problem efficiently. The performance of the proposed algorithm is enhanced using the Taguchi design method. Finally, Adaptive Large Neighbourhood Search (ALNS) algorithm and Variable Neighbourhood Search (VNS) algorithm are considered as two well-known algorithms to test the efficiency of the IALNS algorithm using benchmark problems. Furthermore, a statistical test is conducted to efficiently provide the required comparisons for large-sized problems. It is revealed that the proposed IALNS has a superior performance and can appropriately tackle the problem. Finally, the impacts of the proposed model on cost-saving are evaluated using the proposed IALNS algorithm.

KEYWORDS:

• Time-dependent vehicle routing problem
• multiple depots
• green vehicle routing problem
• improved adaptive large neighbourhood search
• variable neighborhood search

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1 https://neo.lcc.uma.es/vrp/vrp-instances/multiple-depot-vrp-instances/.