An integrated optimization framework for lot sizing and scheduling in sustainable hybrid production

An integrated approach that combines lot sizing and scheduling in production planning can lead to more optimal solutions compared to handling these components independently. Manufacturers today are confronted with the dual challenge of achieving economic efficiency while also addressing environmental sustainability concerns, such as carbon emissions and product reuse through remanufacturing. Furthermore, manufacturers must navigate uncertainties that can significantly impact decision-making in practice. This paper presents an Integrated Lot Sizing and Scheduling (ILS) model that incorporates remanufacturing, carbon emissions, hybrid production lines, and uncertainty to maximize total profit. To the best of our knowledge, this study presents the first mathematical model that simultaneously integrates lot sizing, production sequencing, remanufacturing activities, carbon tax cost considerations, and fuzzy-based uncertainty within a capacitated hybrid production line. The production system is designed with two lines exhibiting distinct characteristics: the green production line generates fewer emissions compared to the regular production line, yet incurs higher production costs. To address the uncertainty surrounding demand, material, and used product acquisition costs, as well as production capacity, the ILS model employs a fuzzy optimization approach. Lingo 18 software is utilized to identify the optimal solution within the model. The findings indicate that variations in the percentage of used products purchased, the percentage of used products remanufactured, carbon tax rates, emissions associated with the green production line, and production costs in the green line significantly influence total profits and carbon emission costs. The policy developed can proficiently manage the scheduling and resource allocation on the hybrid production line by carefully evaluating the balance between production expenses and emission levels. Furthermore, the developed policy effectively coordinates the operations of remanufacturing facilities alongside production facilities. This synchronization enhances overall system performance, optimizing workflows and improving efficiency across the entire production process. • Formulate an integrated lot sizing and scheduling model for sustainable production planning. • Employ a hybrid production system combining regular and environmentally friendly production lines. • Use fuzzy optimization to address uncertainties in demand, cost, and capacity. • Incorporate remanufacturing to recover used products from end customers. • Integrate supplier selection and all-unit discount in the optimization model.

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Publication Details

Journal
Decision Analytics Journal
Published
2026-03-23
DOI
https://doi.org/10.1016/j.dajour.2026.100701
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
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article

An integrated optimization framework for lot sizing and scheduling in sustainable hybrid production

Nughthoh Arfawi Kurdhi, Theresia Sunarni, Wakhid Ahmad Jauhari, Pringgo Widyo Laksono
Decision Analytics Journal
Scheduling and Optimization Algorithms
article

An integrated optimization framework for lot sizing and scheduling in sustainable hybrid production

Nughthoh Arfawi Kurdhi, Theresia Sunarni, Wakhid Ahmad Jauhari, Pringgo Widyo Laksono
article en

Abstract

An integrated approach that combines lot sizing and scheduling in production planning can lead to more optimal solutions compared to handling these components independently. Manufacturers today are confronted with the dual challenge of achieving economic efficiency while also addressing environmental sustainability concerns, such as carbon emissions and product reuse through remanufacturing. Furthermore, manufacturers must navigate uncertainties that can significantly impact decision-making in practice. This paper presents an Integrated Lot Sizing and Scheduling (ILS) model that incorporates remanufacturing, carbon emissions, hybrid production lines, and uncertainty to maximize total profit. To the best of our knowledge, this study presents the first mathematical model that simultaneously integrates lot sizing, production sequencing, remanufacturing activities, carbon tax cost considerations, and fuzzy-based uncertainty within a capacitated hybrid production line. The production system is designed with two lines exhibiting distinct characteristics: the green production line generates fewer emissions compared to the regular production line, yet incurs higher production costs. To address the uncertainty surrounding demand, material, and used product acquisition costs, as well as production capacity, the ILS model employs a fuzzy optimization approach. Lingo 18 software is utilized to identify the optimal solution within the model. The findings indicate that variations in the percentage of used products purchased, the percentage of used products remanufactured, carbon tax rates, emissions associated with the green production line, and production costs in the green line significantly influence total profits and carbon emission costs. The policy developed can proficiently manage the scheduling and resource allocation on the hybrid production line by carefully evaluating the balance between production expenses and emission levels. Furthermore, the developed policy effectively coordinates the operations of remanufacturing facilities alongside production facilities. This synchronization enhances overall system performance, optimizing workflows and improving efficiency across the entire production process. • Formulate an integrated lot sizing and scheduling model for sustainable production planning. • Employ a hybrid production system combining regular and environmentally friendly production lines. • Use fuzzy optimization to address uncertainties in demand, cost, and capacity. • Incorporate remanufacturing to recover used products from end customers. • Integrate supplier selection and all-unit discount in the optimization model.

Decision Analytics JournalVol. 19
Sebelas Maret University (ID)
Responsible consumption and production
Openalex Percentile: Top 11%
Scheduling and Optimization Algorithms
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