Exploring Feasible Optimisation Technique of Packing Measurands in Data Cycle Map

During flight test, a common objective is to collect data from specially instrumented aircraft. Typically several hundreds of measurands (parameters) such as speed, altitude, and pressure, are monitored and telemetered to the ground receiving station for both real-time monitoring and storage for later post-test analysis. Prior to this transmission, measurands are digitally represented and placed in a certain order within a data structure know as Data Cycle Map (DCM). These placements are based on measurands periodicity, sample rate and certain industry standards. Therefore, it is necessary to determine the order of placement before hand. The process of designing data cycle map can be performed manually for few measurands but as the number of measurands increases the process becomes rather complex and time consuming. The need to improve this process has become an interesting topic to explore in operation research group. In the past the problem of designing DCM has been modelled using set covering integer-programming formulation. In this approach measurands (the parameters) are allocated to the map and the DCM design is optimised in terms of the amount of wasted space on the map. This problem is equivalent to Multi Choice Knapsack Problem (MCKP). As number of measurands increases, the solve time increases exponentially. It is therefore NP-hard and clever optimisation technique is needs to solve these problems. The focus of this paper is to investigate a new mathematical approach to strengthen the set-covering model described in the past. It is desired that solution based on branch and bound process can be speed up by generating strengthened LP solution.