Minimizing total carbon footprint and total late work criterion in flexible job shop scheduling by using an improved multi-objective genetic algorithm

摘要

Highlights?A multi-objective flexible job shop scheduling problem is presented to minimize total carbon footprint and total late work criterion.?An improved multi-objective genetic algorithm is proposed to solve the presented bi-objective optimization problem.?The proposed algorithm is superior in finding high quality non-dominated schedules as compared to NSGA-II and SPEA2.?The obtained set of schedules can help managers to differentiate the relationship between total carbon footprint and total late work criterion.AbstractIn scheduling, previous research attention has been directed towards classical-based objective functions, while ignoring environmental-based objective functions. The purpose of this research is to present a multi-objective flexible job shop scheduling problem with the objectives of minimizing total carbon footprint and total late work criterion, simultaneously, as sustainability-ba