Diseño de una metaheurística GRASP en un ambiente flow Shop determinístico biobjetivo

Scheduling is an analytic tool for making decisions that has acquired an important role in manufacturing and services industries. Is the solid foundation of industrial development. For this study, we propose to solve the bi-objective scheduling problem in a deterministic Blocking Permutation Flow Shop (BPFS), that minimizes the makespan and the total tardiness. Flow Shop environments are present in many industries such as chemistry, petrochemicals, assembly, food, circuits, among others. In addition, the analysis of Blocking (due to the limited buffer) and the minimization of two objectives simultaneously make this application closer to real environments. Makespan seeks a better use of machines and Tardiness a higher level of customer services. In this proposal, GRASP metaheuristic will be considered as a multiobjective solution with two different approaches: Pareto Archived Evolution Strategy (PAES), to find the Pareto border between the two objectives and the lexicographical order. The results show that the execution time is a decisive factor to define the approach of the objective function, taking in count that this is a NP-Hard problem. For this experiment, the largest instances tend to get better results with the lexicographic ordering while the small ones find it with GRASP-PAES.

• Autores: Galindo Medina, Kerly Gisell; Ramos Fajardo, Jennifer Alejandra; Yunez Charry, María Juliana
• Tipo de recurso: Trabajo de grado de pregrado
• Fecha de publicación: 2020
• Institución: Pontificia Universidad Javeriana
• Repositorio: Repositorio Universidad Javeriana
• Idioma: spa
• OAI Identifier: oai:repository.javeriana.edu.co:10554/53181
• Acceso en línea: http://hdl.handle.net/10554/53181
• Palabra clave: Scheduling; Flow shop (FS); GRASP; Makespan; Tardiness; Permutation; Blocking; Pareto border; Lexicographical order; PAES; Ingeniería industrial - Tesis y disertaciones académicas; Metaheurística; Algoritmos heurísticos; Programación de la producción
• Rights: openAccess
• License: Atribución-NoComercial-SinDerivadas 4.0 Internacional