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

Tarik Chargui,Mohamed Reghioui,Damien Trentesaux,Abdelghani Bekrar

doi:10.3390/su11113127

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.

Highlights

Nowadays, global optimization of the supply chain is becoming the main goal of many industrial companies, especially the logistics distribution ones
The remainder of this manuscript is categorized as follows: In Section 2, we review the literature related to the Physical Internet, cross-dock truck scheduling, sustainability, and the solving methods for multi-objective problems, especially those related to the truck scheduling in cross-docks
The remaining of the columns shows the results of the two meta-heuristics (MO-VNSSA and MO-VNSTS) which provide optimal results for the first objective F1 and near optimal values for the second objective F2 within fast computational times compared to the ones of CPLEX

Summary

Introduction

Global optimization of the supply chain is becoming the main goal of many industrial companies, especially the logistics distribution ones. The objective is to globally reduce the economical cost and to increase the productivity while taking into consideration the social and environmental aspects. The efficiency and reactivity of the supply chains has become a big challenge for distribution companies to satisfy retailers and customer demands in terms of cost, quality and delivery time [1,2]. With the increase of environmental constraints, supply chain sustainability has emerged as a major approach for logistics firms to enhance their economical, social and environmental sustainability [3,4,5]. In addition to the linkage between all those components of the supply chain, the structure and the configuration of the supply chain has a major impact on the supply chain sustainability [6,7]

Methods

Results

Discussion

Conclusion