Optimizing Perishable and Non-Perishable Product Assignment to Packaging Lines in a Sustainable Manufacturing System: An AUGMECON2VIKOR Algorithm

TL;DR

This paper develops a multi-objective optimization model for assigning perishable and non-perishable products to manufacturing systems, aiming to reduce costs, enhance quality, and lower CO2 emissions, with a novel AUGMECON2VIKOR algorithm demonstrating superior solutions.

Contribution

It introduces a new multi-objective model and an AUGMECON2VIKOR algorithm for sustainable product assignment in manufacturing, considering cost, quality, and environmental impact.

Findings

AUGMECON2VIKOR outperforms AUGMECON2 in Pareto solutions.

The model effectively balances cost, quality, and emissions.

Sensitivity analysis shows positive green impacts on cost and quality.

Abstract

Identifying appropriate manufacturing systems for products can be considered a pivotal manufacturing task contributing to the optimization of operational and planning activities. It has gained importance in the food industry due to the distinct constraints and considerations posed by perishable and non-perishable items in this problem. Hence, this study proposes a new mathematical model according to knowledge discovery as well as an assignment model to optimize manufacturing systems for perishable, non-perishable, and hybrid products tailored to meet their unique characteristics. In the presented model, three objective functions are taken into account: (1) minimizing production costs by assigning the products to the right set of manufacturing systems, (2) maximizing the product quality by assigning the products to the systems, and (3) minimizing total CO2 emissions of the machines. A numerical example is utilized to evaluate the performance of AUGMECON2VIKOR compared to AUGMECON2. The results show that AUGMECON2VIKOR obtains superior Pareto solutions across all objective functions. Furthermore, the sensitivity analysis explores the positive green impacts, influencing both cost and quality.