Iterated local search multi-objective methodology for the green vehicle routing problem considering workload equity with a private fleet and a common carrier

Abstract

A multi-objective methodology was proposed for solving the green vehicle routing problem with a private fleet and common carrier considering workload equity. The iterated local search metaheuristic, which is adapted to the solution of the problem with three objectives, was proposed as a solution method. A solution algorithm was divided into three stages. In the first, initial solutions were identified based on the savings heuristic. The second and third act together using the random variable neighbourhood search algorithm, which allows performing an intensification process and perturbance processes, giving the possibility of exploring new regions in the search space, which are proposed within the framework of optimizing the three objectives. According to the previous review of the state of the art, there is little related literature; through discussions with the productive sector, this problem is frequent due to increases in demand in certain seasons or a part of the maintenance vehicle fleet departing from service. The proposed methodology was verified using case studies from the literature, which were adapted to the problem of three objectives, obtaining consistent solutions. Where cases were not reported in the literature, these could be used as a reference in future research.

Distribution Path Segmentation Using Route Relocation and Savings Heuristics for Multi-Depot Vehicle Routing

“…The operation of the heuristic savings system was tested with several improvements, such as defining new parameters, evaluating penalty multipliers, adding a probabilistic approach, and implementing a post-improvement procedure to control the impact of neighborhood structures. The issue of green vehicle routing was raised as a potential resolution in addition to a multi-objective approach that takes workload equity for both private fleets and common carriers [8]. Numerous optimization heuristics for real-time disruption problems are used to investigate the disruption of the vehicle routing problem [9].…”

Workload Equity in Multi-Period Vehicle Routing Problems

“…In addition, they considered two additional criteria within a multi-objective framework. Since that work, numerous papers have considered workload balance objectives in single-period VRPs with different equity measures (see, e.g., Golden et al 1997;Lee and Ueng 1999;Jozefowiez et al 2009;Lopez et al 2014;Oyola and Løkketangen 2014;Bertazzi et al 2015;Galindres Guancha et al 2018;Va et al 2018;Vega-Mejia et al 2019;Zhang et al 2019;Lehuédé et al 2020;Londono et al 2021). The Min-Max measure and the difference between the maximum and minimum workloads (called Range by Matl et al 2018) are most commonly used.…”

“…The Min-Max measure and the difference between the maximum and minimum workloads (called Range by Matl et al 2018) are most commonly used. When considering distance as the workload metric, Min-Max minimizes the longest route in a solution (see, e.g., Lopez et al 2014), whereas Range minimizes the difference between the longest and shortest route (see, e.g., Londono et al 2021). We refer the reader to Halvorsen-Weare and Savelsbergh (2016), Lozano et al (2016), andMatl et al (2018) for a comprehensive list of equity measures.…”

A greedy heuristic algorithm to solve a VRP-based model for planning and coordinating multiple resources in emergency response to bushfires

“…Their results showed a better solution compared to the Ant Colony System implemented on the same problem in a previous study. Londono et al [21] implemented an iterated local search method in three stages on a green VRP with three objective functions. Their methodology was quite novel in the related literature.…”