Minimizing the energy consumption and the total weighted tardiness for the flexible flowshop using NSGA-II and NRGA

نویسندگان
Nasiri, Mohammad Mahdi ID 1
Rahbari, Ali ID 2
Salmanzadeh, Navid ID 3
Abdollahi, Mojtaba ID 4
Salesi, Sadegh ID 5

1 University of Tehran

2 Department of Industrial Engineering, Alborz Campus, University of Tehran, Tehran, Iran

3 Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran

4 School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

5 School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

doi
چکیده

This paper presents a bi-objective MIP model for the flexible flow shop scheduling  problem (FFSP) in which the total weighted tardiness and the energy consumption are minimized simultaneously. In addition to considering unrelated machines at each stage, the set-up times are supposed to be sequence- and machine-dependent, and it is assumed that jobs have different release times. Two Taguchi-based-tuned algorithms: (i) non-dominated sorting genetic algorithm II (NSGA-II), and (ii) non-dominated ranked genetic algorithm (NRGA) are applied to solve themodel. Six numerical examples with different sizes (small, medium, and large) are used to demonstrate the applicability and to exhibit the efficacy of the algorithms. The results show that the NRGA outperforms significantly the NSGA-II in the performance metrics for all six numerical examples.

کلیدواژه‌ها
Flexible flow shop scheduling, energy consumption, weighted tardiness, Genetic Algorithm, strength Pareto evolutionary algorithm