Abstract:
Outsourcing is becoming increasingly popular in today’s age where customers have higher expectations from suppliers than ever before. Businesses are collaborating to aim to meet customer demand and stay competitive in the market. Some businesses turn to outsourcing. This industry is rapidly growing and faces a unique set of challenges. Customers value flexibility and punctuality in this service provided. In order to do this, logistics providers have to account for the stochastic nature of customer demand and thereby incur additional costs.
The focus of the project is on a transportation based logistics provider that provides transportation-, cross docking- and distribution services to a collection of retail clients. The company is a leveraged logistics provider, which means that it uses its own vehicles as well as vehicles hired from external companies to provide the service. This project aims to investigate ways to reduce the operating costs of a division in a logistics provider company specifically by suggesting the optimal fixed fleet size the company should maintain. This was done by forecasting the anticipated number of vehicles that will be required to meet customers’ service demand for a period of twelve months and finding the optimal fleet size of the 3PL’s fixed fleet. The primary challenge for the 3PL is to maintain their flexibility in the service they provide to clients while introducing stability in their own operations. The report gives a detailed plan that was followed to achieve this goal and outlines the tools and techniques that was applied to obtain the results. Furthermore, a literature study specifically aimed at forecasting and optimization models was done to broaden knowledge and understanding of these subjects.
The results suggests that the 3PL should maintain a fixed fleet size of 129 vehicles in order to meet the following twelve months of anticipated customer service demand. This was calculated as the optimal fixed fleet size that will ensure their customer service level is not affected and lead to a potential saving of almost R 40 000. This analysis will enable the 3PL to make informed decisions regarding the available options they have to reduce their operating expenses.
