Efficient Forecast-Based Routing and Dynamic Time Window Management for Attended Home Deliveries

Abstract

In light of the escalating popularity of online shopping and the urgent need to reduce unnecessary driving to mitigate environmental impacts, it has become increasingly important to provide cost-effective solutions for attended home deliveries. Extensive research efforts have been dedicated to addressing challenges related to integrating demand management and vehicle routing with time windows. In this paper, we present two key contributions. Firstly, we propose an enhanced method for estimating opportunity cost, by leveraging a dynamic-routing and distribution approach that incorporates forecast orders. This approach allows for more accurate revenue-loss assessments, ultimately leading to improved decision-making on the delivery charges. Secondly, we introduce a dynamic slot-combination strategy, aiming to fully exploit the flexibility that customers possess in receiving their delivery, which enhances overall route efficiency and customer satisfaction. Importantly, our proposed augmented time-windows approach can be easily implemented within existing systems, employing standard time windows, without necessitating any strategic changes or complex computational modifications to the routing system. To assess the performance of our proposed approach, we conducted exhaustive experiments on real data. The results demonstrate that our generated solution outperforms both recent and current state-of-the-art approaches in terms of profitability and delivery efficiency. This signifies the effectiveness and practicality of our proposed methodology in addressing the challenges associated with attended home deliveries.