Development of Integrated Multi-objective Green Supply Chain Scheduling Model: Production, Distribution and Heterogeneous Vehicle Routing with Customer Time Windows

In this study, different ways of delivering goods to customers are created and therefore the vehicle routing decisions are added to this issue. In this case, customers must be divided into clusters and each customer assigned to one means of transportation in order to minimize the cost of orders between customers. In this study, the problem of integrated supply chain scheduling is determined by timely delivery of orders, scheduling orders on a machine in a manufacturing system and batch shipment, allocation to multiple heterogeneous transport modes according to capacity, and finally order delivery. To customers in the time window, it aims to minimize the total cost of distributing orders and the constant and variable costs of fuel and carbon emissions of the vehicle and the total time delay of customer orders.

The problem programming model is a mathematical model of complex nonlinear integer and has been used for solving multi-objective meta-algorithms MOPSO and NSGA-II.

The results show that NSGA-II algorithm performs well.

This research reduces the costs of production, distribution, inventory maintenance and fuel consumption. It can also help reduce product inventory and maintenance costs.