Next Article in Journal
Application of Time-Lapse Ion Exchange Resin Sachets (TIERS) for Detecting Illegal Effluent Discharge in Mixed Industrial and Agricultural Areas, Taiwan
Next Article in Special Issue
A Methodology to Assess the Suitability of Food Processing Technologies for Distributed Localised Manufacturing
Previous Article in Journal
Evaluating Impacts of Overweight in Road Freight Transportation: A Case Study in Brazil with System Dynamics
Previous Article in Special Issue
An Enhanced Estimation of Distribution Algorithm for Energy-Efficient Job-Shop Scheduling Problems with Transportation Constraints
Article Menu
Issue 11 (June-1) cover image

Export Article

Open AccessArticle

Multi-Objective Sustainable Truck Scheduling in a Rail–Road Physical Internet Cross-Docking Hub Considering Energy Consumption

1
LAMIH, UMR CNRS 8201, Université Polytechnique Hauts-de-France, Le Mont Houy, 59313 Valenciennes, France
2
RSAID, ENSATe, University of Abdelmalek Essaadi, Tétouan 93000, Morocco
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(11), 3127; https://doi.org/10.3390/su11113127
Received: 15 May 2019 / Revised: 28 May 2019 / Accepted: 29 May 2019 / Published: 3 June 2019
(This article belongs to the Special Issue Sustainable Intelligent Manufacturing Systems)
  |  
PDF [1308 KB, uploaded 3 June 2019]
  |  

Abstract

In the context of supply chain sustainability, Physical Internet (PI or π ) was presented as an innovative concept to create a global sustainable logistics system. One of the main components of the Physical Internet paradigm consists in encapsulating products in modular and standardized PI-containers able to move via PI-nodes (such as PI-hubs) using collaborative routing protocols. This study focuses on optimizing operations occurring in a Rail–Road PI-Hub cross-docking terminal. The problem consists of scheduling outbound trucks at the docks and the routing of PI-containers in the PI-sorter zone of the Rail–Road PI-Hub cross-docking terminal. The first objective is to minimize the energy consumption of the PI-conveyors used to transfer PI-containers from the train to the outbound trucks. The second objective is to minimize the cost of using outbound trucks for different destinations. The problem is formulated as a Multi-Objective Mixed-Integer Programming model (MO-MIP) and solved with CPLEX solver using Lexicographic Goal Programming. Then, two multi-objective hybrid meta-heuristics are proposed to enhance the computational time as CPLEX was time consuming, especially for large size instances: Multi-Objective Variable Neighborhood Search hybridized with Simulated Annealing (MO-VNSSA) and with a Tabu Search (MO-VNSTS). The two meta-heuristics are tested on 32 instances (27 small instances and 5 large instances). CPLEX found the optimal solutions for only 23 instances. Results show that the proposed MO-VNSSA and MO-VNSTS are able to find optimal and near optimal solutions within a reasonable computational time. The two meta-heuristics found optimal solutions for the first objective in all the instances. For the second objective, MO-VNSSA and MO-VNSTS found optimal solutions for 7 instances. In order to evaluate the results for the second objective, a one way analysis of variance ANOVA was performed. View Full-Text
Keywords: Physical Internet; cross-docking; Rail–Road; sustainability; truck scheduling; energy consumption; Multi-Objective Programming; Lexicographic Goal Programming; hybrid meta-heuristics Physical Internet; cross-docking; Rail–Road; sustainability; truck scheduling; energy consumption; Multi-Objective Programming; Lexicographic Goal Programming; hybrid meta-heuristics
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Chargui, T.; Bekrar, A.; Reghioui, M.; Trentesaux, D. Multi-Objective Sustainable Truck Scheduling in a Rail–Road Physical Internet Cross-Docking Hub Considering Energy Consumption. Sustainability 2019, 11, 3127.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top