Hybrid Flow Shop with Unrelated Machines, Setup Time, and Work in Progress Buffers for Bi-Objective Optimization of Tortilla Manufacturing

Algorithms

Andrei Tchernykh¹  Ricardo Salomon-Torres²  Francisco Villalobos-Rodríguez²  VictorHugo Yaurima-Basaldua² 

[1] Computer Science Department, CICESE Research Center, Ensenada 22860, Mexico;Software Engineering, Sonora State University, San Luis Rio Colorado, Sonora 83455, Mexico;

关键词: multiobjective genetic algorithm;    hybrid flow shop;    setup time;    energy optimization;    production environment;   

DOI  :  10.3390/a11050068

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown