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Abstract

Strategic system logistics business entails the importance of regulating truck pooling facilities and allocating the trucks for cost optimization goals. Regulators and investors must consider spatial constraints such as the supply-demand gap and service distance. Little attention has been paid to developing decision logistics models, particularly truck pooling and allocation decisions. In this study, the FFOA and GIS were used to determine the spatial component of truck pooling decisions, providing a scenario for origin pooling and delivery distance. The model evaluates truck allocation to each city, a distance vector, a spatial factor, and city demand are used for the cost optimization goal. The results show that the FFOA model successfully defines the optimal truck allocation for each truck pooling site with a cost. The managerial implication in developing a sharing economy concept for truck logistics is to use the study's framework model result to solve challenges in truck logistics.

Keywords

Trucks Pooling Trucks Allocation FFOA GIS Optimization Spatial

Article Details

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Siahaan, B. P., Simatupang, T. M., Okdinawati, L., Yang, C.- kai, & Nugroho, D. (2022). Trucks Pooling and Allocation in TSE Concept Using GIS Spatial and Novel FFOA. Ilomata International Journal of Management, 3(4), 486-500. https://doi.org/10.52728/ijjm.v3i4.571

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