Multi-objective flexible job shop scheduling problem with triple bottom line theory-based sustainable objectives

Abstract

The triple bottom line theory (TBL) is widely used in the field of sustainable development research. Based on the triple bottom line theory, this paper investigates a multi-objective flexible job shop scheduling problem with the consideration of sustainable objectives. A multi-population evolutionary algorithm with single-objective guide (MPEA/SG) is modified to solve this problem effectively by extending the MPEA/SG to discrete optimization problems. Our experiments show that considering TBL-based objectives in job shop scheduling is more conducive to the sustainability of the production process, and can effectively reduce the carbon footprint, E/T penalty cost and income difference.