Fleet Assignment Using Collective Intelligence

Product distribution theory is a new collective intelligence based framework for analyzing and controlling distributed systems. Its usefulness in distributed stochastic optimization is illustrated here through an airline fleet assignment problem. This problem involves the allocation of aircraft to a set of flight legs in order to meet passenger demand, while satisfying a variety of linear and non-linear constraints. Over the cause of the day, the routing of each aircraft is determined in order to minimize the number of required lights for a given fleet. The associated flow continuity and aircraft count constraints have led researchers to focus on obtaining quasi-optimal solutions, especially at large scales. This paper proposes the application of this new stochastic optimization algorithm to a non-linear objective cold start fleet assignment problem. Results show that the optimizer can successfully solve such highly constrained problems.