A multi-item flexible-packaging model to minimise the cost of lost units and CO2 emissions for flexible flow shop scheduling

Abstract

Efficient production processes are crucial in satisfying customer requirements and achieving operational superiority. This implies synchronisation between links in a supply chain to adapt to dynamic market needs. Due to its complexity, flexible flow shop scheduling has attracted much concern from academics and practitioners. In addition, sustainability issues have gained attention since efficient energy management enhances economic competitiveness and ecological responsibility. However, research often integrates flexible flow shop scheduling with distribution, leaving aside other stages, such as finished product packaging. Therefore, this paper proposes a model to optimise scheduling and package sizing considering multiple products and package sizes to minimise the cost of lost units and carbon dioxide emissions. A genetic algorithm was developed to find high-quality solutions based on minimising the Mean Ideal Distance. An experimental design was conducted to determine the parameters influencing the algorithm’s performance. The results emphasised the impact of the crossover rate, mutation rate, and number of generations. Also, sensitivity analyses were performed to explore the relationship between the package types, inventory and lost units. Results highlighted the advantage of diverse package sizes in aligning dispatched final products with demand. Furthermore, a relation between inventory and lost units across demand levels was observed, underscoring the impact of overscheduling in production systems.