Parallel, multistage model for enterprise system planning and design

This paper describes a parallel, multistage optimization approach for enterprise system design and planning where the design of a system is linked with its planing and operations (resource allocation). Our approach is composed of two parts: a multistage formulation and a task-parallel algorithm. The formulation utilizes the quasi-separability of the multistage decision making structure, i.e., allowing relaxation by defining the linking variables for adjacent stages of decision making. The task-parallel algorithm enables optimal load balancing of the tasks, and it is validated in the demonstration case where an airline plans to introduce multiple new aircraft to capture dynamically changing travel demand. A linearly increasing computational load is assumed as the number of stages increases due to the complexity added onto the upcoming future stages in the optimization processes. The proposed task parallel algorithm demonstrates significant speedups and parallel performances by utilizing this linearity.