Green vehicle routing and dynamic pricing for scheduling on-site services

In this paper, we study a problem where a company sends engineers with vehicles to customer sites to provide services. Customers request the service through a website or by calling a call centre and the company needs to allocate the service tasks to time windows and decide on how to schedule these jobs to their vehicles. We propose a new approach to this problem which applies low-emission vehicle routing techniques with dynamic pricing to reduce CO2 emissions and maximise profit. When a customer requests a service, the company will provide the customer with different service time-window options and their corresponding prices. Prices are differentiated to influence the customer's choice. To help the company in determining the prices, our approach solves the problem in two phases. The first phase solves a time-dependent vehicle routing model with the objective of minimising CO2 emissions for each of the time window options and the second phase solves a dynamic pricing model to determine the service prices for these options to maximise profit. Metaheuristic methods are applied for real-life business applications which enable the solution framework to be applied online where shorter computational time is required. The approach is tested through numerical experiments. Results show that dynamic pricing leads to a reduction in CO2 emissions and an improvement in profit.