Joint-optimization of a truck appointment system to alleviate queuing problems in chemical plants

Numerous studies have proposed the use of a Truck Appointment System (TAS) to alleviate traffic congestion at logistics sites. Unfortunately, the implementation of such a system was often optimized based on the interest of a single stakeholder. Meanwhile, long truck queues have been observed in many chemical plants. This study aims to evaluate the TAS performances to mitigate traffic congestion in chemical plants from the multi-stakeholder perspective. We proposed a joint-optimization model to accommodate various interests on the site. An improved fluid-flow approximation was developed to estimate the time-dependent performance of the system. The results suggest that the benefit of TAS is mostly enjoyed by the site manager through the reduction of site overtime, while the benefits for trucking companies are found to be marginal. Through numerical experiments, we show that the proposed joint-optimization model is effective in redistributing the benefits of TAS across the stakeholders, while keeping the total logistics costs to a minimum.