Tailored Iterated Greedy metaheuristic for a scheduling problem in metal 3D printing

Abstract

This article contributes to the additive manufacturing-based production planning literature by developing a Mixed-Integer Linear Programming (MILP) formulation for the Identical Parallel 3D-Printing Machines Scheduling Problem considering batching, multiple build platforms of restricted sizes, and sequence-independent setup times. Besides, a customized metaheuristic, named the Tailored Iterated Greedy (TIG) Algorithm is developed to solve the new optimization problem. TIG’s performance is evaluated through extensive numerical analysis and using a new testbed. It is shown that the customized computational mechanisms improve the optimization performance; statistical analysis is supportive of the significance of the resulting improvements. The developed mathematical model and optimization algorithm can be considered the basis for future developments in the optimization literature of additive manufacturing.