%0 Journal Article
%T Hybrid Flow Shop with Unrelated Machines, Setup Time, and Work in Progress Buffers for Bi-Objective Optimization of Tortilla Manufacturing
%A Andrei Tchernykh
%A Francisco Villalobos-Rodr¨ªguez
%A Ricardo Salomon-Torres
%A Victor Hugo Yaurima-Basaldua
%J Algorithms | An Open Access Journal from MDPI
%D 2018
%R https://doi.org/10.3390/a11050068
%X Abstract We address a scheduling problem in an actual environment of the tortilla industry. Since the problem is NP hard, we focus on suboptimal scheduling solutions. We concentrate on a complex multistage, multiproduct, multimachine, and batch production environment considering completion time and energy consumption optimization criteria. The production of wheat-based and corn-based tortillas of different styles is considered. The proposed bi-objective algorithm is based on the known Nondominated Sorting Genetic Algorithm II (NSGA-II). To tune it up, we apply statistical analysis of multifactorial variance. A branch and bound algorithm is used to assert obtained performance. We show that the proposed algorithms can be efficiently used in a real production environment. The mono-objective and bi-objective analyses provide a good compromise between saving energy and efficiency. To demonstrate the practical relevance of the results, we examine our solution on real data. We find that it can save 48% of production time and 47% of electricity consumption over the actual production. View Full-Tex
%K multiobjective genetic algorithm
%K hybrid flow shop
%K setup time
%K energy optimization
%K production environment
%U https://www.mdpi.com/1999-4893/11/5/68