Integrated optimization of transportation, inventory and vehicle routing with simultaneous pickup and delivery in two-echelon green supply chain network

The economic concern, environmental awareness related legislations, and potential recycling benefits are the main motives that have changed the dimension of supply chain network with environmentally effective transportation and efficient scrap collection system. This paper investigates the two echelon supply chain network of the battery manufacturing industry. This deals with an integrated optimization procedure for solving the green transportation problem and inventory problem in the first echelon, and the capacitated multi depot (Distribution center/Collection center) heterogeneous green vehicle routing problem with simultaneous pickup and delivery in the second echelon. The minimization of the green objective function comprising inventory carrying cost, transportation cost and carbon emission cost are considered in this work. The focus of this paper is to formulate the problem in the Mixed Integer NonLinear Programming model and to solve the four problem instances (P1 e P4) using GAMS 23.5 and Simulated Annealing Algorithm (SAA) with swap neighbourhood solution method. The experimental results show that the integrated approach with SAA provides a better solution than the sequential approach. The robustness test is carried out with four typical problem instances which show that the proposed SAA provides near optimal solutions. The model analysis is demonstrated with different components of the objective function which will help the top management to take appropriate decisions in the context of cost savings. The performance comparison reveals that the proposed SAA (SAA-1) has given better results than the Simulated Annealing Algorithm with insertion method (SAA-2). (C) 2020 Published by Elsevier Ltd.

Automated summary

This study investigates the optimization problem in the supply chain network of the battery manufacturing industry, focusing on reducing overall costs and carbon emissions through green transportation, inventory management, and green vehicle routing. The integrated approach with Simulated Annealing Algorithm was found to provide better solutions, assisting top management in decision-making.