Contextual bandits-guided local search for solving air cargo palletisation problem
研究了航空货运中如何高效地将货物分配到集装器，提出12种基于上下文赌博机引导的局部搜索方法，以最小化成本和未用体积，并考虑分组、定位和兼容性约束。
In this paper, we address the challenges of efficiently assigning items to Unit Load Devices within the air cargo industry. We present a comprehensive formulation of the three-dimensional air cargo palletisation problem, focussing on cost minimisation and incorporating grouping, positioning, and compatibility constraints. We propose a set of 12 resolution approaches that utilise contextual bandits-guided local search heuristics. We conduct a thorough benchmark experiment to evaluate the performance of our proposed methods. Two objective functions, namely unused volume and costs are employed to underscore the significance of cost minimisation in air cargo palletisation. Furthermore, we address instances encompassing grouping, positioning, and compatibility constraints, enabling us to explore the managerial insights these constraints offer and assess the benefits of integrating cost-reduction strategies. The findings provide valuable insights for decision-makers involved in optimising air cargo palletisation operations.