Applying mixed-integer simulation optimization for tactical design decisions of robotic sorting system with guaranteed security level to combat illicit trade

Abstract

With the increasing frequency of online e-commerce and free trade, opportunities and amounts for illicit trade have significantly grown, causing serious harm to the economies, societies, environments, and politics of various countries. Due to outdated and obsolete parcel sorting procedures and equipment, logistics providers handling international import parcels, particularly postal service systems, have become vulnerable entry points for illicit goods. Therefore, this study aims to explore and develop tactical design decisions for a robotic sorting system (RSS) with a guaranteed security level to effectively combat illicit trade and goods entering through international import operations. A mixed-integer stochastic optimization model is formulated to derive optimal tactical solutions, including the number of autonomous mobile robots (AMRs) and inspection personnel, the allocation of drop-off points, and the screening probabilities of inspection stations, to minimize system costs while meeting a specified security threshold. Since the objective function of this model is not analytically available, a high-resolution RSS stochastic simulation model is first constructed to estimate this performance measure. Then, a novel mixed-integer simulation optimization algorithm, namely a combination of optimal computing budget allocation-based ranking and selection procedure and adaptive particle and hyperball search (ORS-APHS), is developed to speed up convergence near-optimal tactical design decisions under a limited simulation budget. We collaborate with Chunghwa Post Company in Taiwan to analyze algorithm efficiency and identify key factors influencing total cost and tactical design decisions to combat illicit trade according to their newly implemented international parcel sorting system. Computational experiments demonstrate that the proposed ORS-APHS algorithm outperforms two common existing methods (Genetic Algorithm and Tabu Search) in terms of effectiveness and efficiency. The sensitivity analysis results indicate that changes in the predetermined system security levels, adjustments in the number of available AMRs, variations in physical re-inspection times, and the distribution of drop-off points for arriving parcels all have significant impacts on total system costs and tactical design solutions. To enhance the security of the RSS system in combating illicit trade, the predetermined system security level is particularly a critical factor in determining the screening probabilities of inspection stations. Decision-makers can leverage the managerial insights and guidelines derived from sensitivity analysis to formulate optimal tactical design plans for the RSS system with a guaranteed security level in the future.