Optimization of the Transportation Problem in the Covid Pandemic with Time-Window Vehicle Routing Problem

Abstract

Logistics is one of the most important factors in any country and it has become a crucial topic due to the significant effect of Covid 19 on the world economics. Since the beginning of time, logistics is a critical link for products circulation throughout the world. When the Covid 19 pandemic came, logistics is becoming an essential role in preventing supply chain disruption. Meanwhile, transportation activity accounts for the highest portion in logistics. Therefore, improving the transportation system and optimizing the delivery method of goods are essential not only in the pandemic but also in any normal business situation. This paper focuses on optimizing the vehicle routing problem with the time window (VRPTW) by Genetic algorithm (GA) since the receiving time of the customer has some boundaries and restrictions. Furthermore, our VRPTW model include vehicle selection algorithm, which will automatically select the most efficient fleet from the set of vehicles with different capacity. This paper analyzes the application of the algorithm to GK logistics-a Vietnamese logistics company, compared to common direct transportation. The result proves that VRPTW is more efficient in term of distance, travel time and vehicle used. Research purpose: There are many transportation problems such as time constraints, capacity constraints, pickup , and delivery constraints, which create many difficulties for transport routers. Finding the vehicle routing is always big issue of any logistics company and manufactures not only in the pandemic but also in any normal business situation. Many enterprises should determine vehicles route allocation to minimize costs by considering capacity and time windows of customers' requirements. Therefore, this paper aims to develop the vehicle routing problem with time windows and selecting the appropriate fleet of trucks to minimize the total distribution cost through finding optimal routes and satisfy the customer demand at specific of receiving time. In this article, the genetic algorithm is applied to solve and optimize vehicle routing problem with hard-time window. The algorithm will be tested and compared with direct transportation method in experiment section. Vehicle routing problem is based on integrating vehicles that deliver goods in the transport network affected by the time. The time window refers to time slot when the fleet reaches the customer's node. Two types of time windows impose each vehicle delivering the goods to the customers within a specific time interval. The vehicle may not arrive at the customer's node closing time and before node open time. The best route must be on time and follow disciplined capacity as well as minimum distance and cost. Research motivation: In recent years, E-commerce is developing rapidly in all over the world. Transportation plays an important role in delivering goods to customer and has a close relationship with E-commerce. Vietnam is among Asian countries having fastest growth in E-commerce. E-commerce has been developed sharply in recent years, since more and more people using the internet to purchase goods. Especially, the percentage of people doing online shopping has increased much more in the Covid 19 pandemic. When customers place orders from supermarkets and E-commerce companies, the supermarkets or E-commerce companies make a plan for delivery. They might manage the transportation activities or outsource to a 3PL provider. Furthermore, Logistics plays an important role in preventing broken supply chain. Transportation should manage the operation not only to meet the customer requirements at the right place, right time, and provide the right quality and but also to minimize the operation costs. As a result, providing cost-effective and efficient service is the top target of any logistics enterprise. In addition, the required receiving time should be strict during the pandemic thus the time window of receiving order also should be included in the research. Therefore, the motivation of this paper is developing the transportation model that minimize transportation distance, optimize capacity but still can meet the customers' requirements in term of time windows and transportation quantity.