Promoting Two-sided Fairness in Dynamic Vehicle Routing Problem (2405.19184v1)

Abstract: Dynamic Vehicle Routing Problem (DVRP), is an extension of the classic Vehicle Routing Problem (VRP), which is a fundamental problem in logistics and transportation. Typically, DVRPs involve two stakeholders: service providers that deliver services to customers and customers who raise requests from different locations. Many real-world applications can be formulated as DVRP such as ridesharing and non-compliance capture. Apart from original objectives like optimising total utility or efficiency, DVRP should also consider fairness for all parties. Unfairness can induce service providers and customers to give up on the systems, leading to negative financial and social impacts. However, most existing DVRP-related applications focus on improving fairness from a single side, and there have been few works considering two-sided fairness and utility optimisation concurrently. To this end, we propose a novel framework, a Two-sided Fairness-aware Genetic Algorithm (named 2FairGA), which expands the genetic algorithm from the original objective solely focusing on utility to multi-objectives that incorporate two-sided fairness. Subsequently, the impact of injecting two fairness definitions into the utility-focused model and the correlation between any pair of the three objectives are explored. Extensive experiments demonstrate the superiority of our proposed framework compared to the state-of-the-art.

• The paper introduces 2FairGA, a novel genetic algorithm that integrates two fairness measures into the dynamic vehicle routing problem.
• It extends conventional approaches by balancing service provider and customer objectives alongside utility optimization.
• Extensive experiments demonstrate that 2FairGA significantly outperforms state-of-the-art methods in promoting both fairness and efficiency.

The paper "Promoting Two-sided Fairness in Dynamic Vehicle Routing Problem" addresses the Dynamic Vehicle Routing Problem (DVRP), an extension of the classic Vehicle Routing Problem (VRP) which is critical in the fields of logistics and transportation. Unlike traditional VRPs, DVRPs involve two main stakeholder groups: service providers who deliver services, and customers who request services from various locations. Common applications of DVRP include ridesharing and non-compliance capture.

A key challenge addressed in this paper is the consideration of fairness from the perspectives of both service providers and customers. Previous work on DVRP has typically focused on achieving fairness for one stakeholder group, overlooking the necessity of balancing fairness for both sides. This imbalance can result in potential dissatisfaction and disengagement from service providers and customers, culminating in detrimental financial and social consequences.

To address this gap, the authors introduce a novel framework called the Two-sided Fairness-aware Genetic Algorithm (2FairGA). This framework extends the conventional genetic algorithm approach, which primarily optimizes for utility, to encompass multiple objectives including two-sided fairness. Specifically, 2FairGA integrates two distinct fairness definitions into the utility optimization model and investigates the interactions and trade-offs between these objectives.

The research thoroughly examines the effects of incorporating two-sided fairness into the DVRP utility model. The authors analyze the correlations between pairs of the three primary objectives: utility optimization and the two fairness measures. Through extensive experiments, the paper demonstrates that the proposed 2FairGA framework significantly outperforms existing state-of-the-art methods.

Overall, this work offers a substantial contribution to the field by highlighting the importance of two-sided fairness in DVRP scenarios and providing a robust algorithmic solution to balance multiple objectives effectively. This makes it a crucial read for researchers and practitioners aiming to enhance fairness and efficiency in dynamic logistics and transportation systems.