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Optimization and incorporating of green traffic for dynamic vehicle routing problem with perishable products

Authors
  • Talouki, Reza Zakaryaei1
  • Javadian, Nikbakhsh2
  • Movahedi, Mohammad Mehdi1
  • 1 Department of Industrial Management, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
  • 2 Mazandaran University of Science and Technology,
Type
Published Article
Journal
Environmental Science and Pollution Research
Publisher
Springer-Verlag
Publication Date
Mar 10, 2021
Pages
1–19
Identifiers
DOI: 10.1007/s11356-021-13059-6
PMID: 33689127
PMCID: PMC7943401
Source
PubMed Central
Keywords
License
Unknown

Abstract

In view of the significance of transportation management and logistics in the economic concept and raising the productivity of production systems, well-timed procurement of perishable materials and goods is determined as a pivotal prerequisite for economic and environmental development. Since the perishable goods produced must be made delivered to consumers as early as possible on account of the limited lifespan, thus, the vulnerability of these products is extremely high, owing to the high cost of transportation as well as the environmental impacts. So that solves this problem, this study represents a problem of dynamic green vehicle routing of perishable products in green traffic conditions that optimizes the total cost for a dynamic transportation network and minimizes environmental influences, and increases customer satisfaction. The introduced model is implemented in light of time windows as a trustworthy solution for monitoring the dynamic logistics process and attaining instantaneous information on the basis of the green traffic situation and travel duration, which is commonly known by the Logit function. Assuming the three-objective programming model, we consider a new improved algorithm developed for a novel augmented ε-constraint heuristic approach. Furthermore, robust optimization has been conducted for the established problem to tackle with uncertainties. Uncertainties are included demand and economic parameters. Eventually, to validate the proposed model, a case study was carried out at Kaleh Amol Dairy Company in Iran. The conclusions of sensitivity analysis by implementing the model in the real world indicate that the model and approach presented in various uncertainty scenarios have high flexibility.

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