Basic Ship-Planning Support System Using Big Data in Maritime Logistics for Simulating Demand Generation

Dimas Angga Fakhri Muzhoffar,Yusuke Miyake,Shun Kawamura,Kunihiro Hamada,Yujiro Wada

doi:10.3390/jmse10020186

Dimas Angga Fakhri Muzhoffar, Yusuke Miyake + Show 3 more

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https://doi.org/10.3390/jmse10020186

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Abstract

Dynamic changes in the global market demand affect ship development. Correspondingly, big data have provided the ability to comprehend the current and future conditions in numerous sectors and understand the dynamic circumstances of the maritime industry. Therefore, we have developed a basic ship-planning support system utilizing big data in maritime logistics. Previous studies have used a ship allocation algorithm, which only considered the ship cost (COST) along limited target routes; by contrast, in this study, a basic ship-planning support system is reinforced with particularized COST attributes and greenhouse gas (GHG) features incorporated into a ship allocation algorithm related to the International Maritime Organization GHG reduction strategy. Additionally, this system is expanded to a worldwide shipping area. Thus, we optimize the operation-level ship allocation using the existing ships by considering the COST and GHG emissions. Finally, the ship specifications demanded worldwide are ascertained by inputting the new ships instance.

Highlights

Economic growth creates dynamic changes in the global market, including the maritime industry
We suggest two attributes to be considered in the ship allocation algorithm: ship cost (COST) aspects and greenhouse gas (GHG) emissions
For the GHG emissions aspect, case study 2b achieved a 14.8% reduction, which replaced by new ships

Summary

Introduction

Economic growth creates dynamic changes in the global market, including the maritime industry. With the reduction in cost of data collection tools, a large amount of data can be obtained from various sources and formats [2,3] This is significant for a broader understanding of the current and future conditions of various industries. Big data are being generated through advancements in navigation systems [5,6]. An AIS transponder transmits a ship’s identification number, position, course, speed, and destination. These systems uphold the digitalization of previously analog-stored data, such as ship specifications, port limitations, and sailing routes [8]. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations

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