Integrating Strategic and Tactical Decisions to Robust Designing of Cellular Manufacturing under Uncertainty: Fixed Suppliers in Supply Chain

Abstract

Cellular manufacturing (CM) has been identified as an innovative practice for manufacturer to achieve efficiency as well as flexibility under an uncertain environment. This study addresses a new mathematical robust model for a cellular manufacturing problem integrated with tactical aspects under supply chain network characteristics in the presence of uncertain internal parameter (processing times) and external parameter (demands). The model aims to minimize total cost consisting expected value and variance of tactical cost (scheduling), strategic cost (employment of suppliers in supply chain network) to produce exceptional elements as well as the cost of resource underutilization. The model can give up a series of the solutions that are less sensitive to the changes in input data. To solve the robust model, an efficient hybrid method based on new combination of genetic algorithm (GA), simulated annealing (SA) in a parallel structure are proposed under an optimization rule. The effectiveness of the proposed model is demonstrated by numerical results and the trade-off between solution robustness and model robustness is also analyzed.

A robust optimization approach for an integrated dynamic cellular manufacturing system and production planning with unreliable machines

“…It is a comprehensive model that can be used in many real-world applications. • A robust optimization approach [46] is developed for the new presented model.…”

“…To cope with over conservatism and nonlinearity issues in previous studies, Bertsimas and Sim [44,45] proposed a linear robust optimization. In the CMS field,Ghezavati et al [46] proposed a mathematical model including cell formation and group scheduling problems in a supply chain framework. They solved the proposed model by applying an approach based on Mulvey et al [38] considering part processing time and demand uncertainty.…”

A Novel Robust Possibilistic Cellular Manufacturing Model Considering Worker Skill and Product Quality

“…In addition, employing the robust optimization, Ghezavati et al [31] presented a novel mathematical robust optimization model for a CMS integrated with tactical aspects regarding supply chain network features in the presence of imprecise processing time and demand parameters. Forghani et al [32] provided a novel robust optimization approach to address data uncertainty.…”