Optimization of ULD Load Planning Using MILP: Mixed Integer Linear Programming

The spreading of the COVID-19 virus limits the transportation services capacity, which heavily impacts the logistics business. In air freight services, flight arrangement relies on the number of passengers traveling from/to different destinies. Soon after COVID-19 vigorously spread, minor flight operation and transportation charges suddenly increased to cover higher operating costs while carriers aimed to maintain a consistent profit. The objective of this paper is to minimize high air freight expenses and reduce manual load planning by implementing MILP (Mixed integer linear programming), which supports automating cargo load planning. Moreover, 3D Load Packer is introduced to validate the output of optimized value received from CPLEX Optimization Studio to ensure loading feasibility. As a result, this study provides significant benefits in load planning speed and profit enhancement.