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Affiliation(s)

1. Singapore University of Social Sciences, School of Business, Singapore
2. Singapore Management University, School of Information Systems, Singapore

ABSTRACT

Human’s impact on earth through global warming is more or less an accepted fact. Ocean freight is estimated to contribute 4-5% of global carbon emissions. Many manufacturing companies that transfer ship goods through full container loads found themselves under-utilizing the containers and resulting in higher carbon footprint per volume shipment. One of the reasons is the choice of non-ideal container sizes for their shipments. In this paper, we first provide an Integer Programming model to minimize the companies’ shipping carbon footprints by selecting the ideal container sizes appropriate for their shipment volumes. Secondly, we proposed a strategy to minimize the carbon footprint by consolidating the shipments in the same country from multiple domestic locations at a port of loading by road freight, before the international sea shipment. A mixed-Integer Programming model has been developed to determine if one should ship each shipment separately or have shipments consolidated first before being shipped. Consolidation fills up the containers more efficiently that reduces the overall carbon footprint. Computational results using real-world data indicates a significant 13.4% reduction carbon emission when selecting the optimal combinations of different sizes of containers and an additional 12.1% reduction in carbon emission when shipment consolidation is applied.

KEYWORDS

Carbon emission, data analytics, container consolidation, sustainability, optimization, ocean freight, supply chain management

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