Development of a decision support system for air-cargo pallets loading problem: A case study

摘要

This paper presents a two-phase intelligent Decision Support System (DSS) for Air-Cargo Loading Problem (ACLP). This problem can also be viewed as three dimensional, non-identical, multiple bin-packing problem because of the different shapes and specification for the air cargo pallets. Phase-I of the proposed decision support system discusses the Linear Programming (LP) model to decide the lower bound for global minimum cost of pallets to load the available cargo based on its weight and volume. Phase-II heuristic of the proposed system efficiently loads the cargo-boxes and generates the loading plan of each pallets with minimum deviation from the lower bound, decided in earlier phase-I, would be the most suited one. The contribution of this paper lies in developing a new approach for the three-dimensional loading plan of the air cargoes on the different shaped and sized pallets. The constraints related to the shape and size of the pallets, related to the airlines and the shipping destination are also taken in account in the proposed system, which are not adequately discussed in the previous literatures. For ranking of cargo-boxes, a method of rank revision based on left empty-space has been suggested. The proposed DSS has been implemented on the real time data sets taken from freight forwarding company. The data sets contain the information about the 54 different classes of the total 671 cargo-boxes. The problem considered in this paper is more complex than the some discussed in the literatures. At number of instances, the developed system has successfully loaded the pallets up to the 90% and above by volume.