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

Abstract

Dynamic changes in the global market demand affect ship development. Correspond-ingly, big data have provided the ability to comprehend the current and future conditions in nu-merous 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. Pre-vious 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 strat-egy. 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 emis-sions. Finally, the ship specifications demanded worldwide are ascertained by inputting the new ships instance.