Publication Type

Conference Proceeding Article

Publication Date

9-2016

Abstract

Purpose: Many manufacturing companies that 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. Consolidation fills up the containers more efficiently that reduces the overall carbon footprint. The objective of this paper is to support decisions on selection of appropriate combination of container sizes and shipment consolidation for a manufacturing company. We develop two-steps model which first takes the volumes to be shipped as an input and provide the combination of container sizes required; then evaluate possibility of shipment consolidation from multiple ports (of loading) within the same country to the same destination (port of discharge). In both steps, the objective function is to minimize carbon footprint by applying linear/integer programming. Only consolidation within the same country is considered due to practical considerations to avoid the need for cross border clearances.Design/Methodology/Approach: 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.Findings: Computational results using real-world data will be showcased. Originality/Value: Optimize the container size for shipment for a manufacturing company and consolidating the shipments within the same country.Practical Implications: We verify our model with a real-world business case (and data) in the consumer product manufacturing industry. By applying the proposed approach and models, the company can reduce the carbon footprint by 13.4% by using the optimal container size and further reduce the carbon footprint by 12.1% from consolidation of shipments as compared to the current practice without optimization.

Keywords

sustainability, optimization, ocean freight, supply chain management

Discipline

Computer Sciences | Operations Research, Systems Engineering and Industrial Engineering | Transportation

Research Areas

Intelligent Systems and Decision Analytics

Publication

Proceedings of the International Conference on Logistics and Transport: 8th ICLT 2016, September 6-8, Singapore

First Page

10

Last Page

10

Publisher

ICLT

City or Country

Singapore

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Comments

Abstract published in Proceedings. Full paper provided by author.

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