MOL Group Successfully Develops Car Carrier Allocation/Loading Plan With AI
An allocation plan for a vessel and a cargo loading plan for car carriers which is based on ‘mathematical optimization’ has been developed by Mitsui O.S.K. Lines, Ltd. (MOL) and its group company MOL Information Systems, Ltd. announced that, along with Associate Professor Shunji Umetani of Graduate School of Information Science and Technology, Osaka University.
MOL can now with this advance technology complete the allocation of vessels and loading plans quicker than ever.
Around 100 car carriers and around 5,000 standard passenger cars, cargo capacity per ship is operated by MOL. The transportation and logistics pattern of automakers and other shippers has been changing. Efficiency in vessel allocation and loading of cargo are of at most importance to make sure that the fleet is operating in the most efficient way thereby meeting customer requirements.
For example, the safety and efficiency of the cargo operations are affected by the deck and the hold where the cargo is loaded, when the vessel is calling a number of loading and unloading ports. The order of cargo loading/unloading and hull balance during the voyage has to be considered. A longer time is taken to develop a plan for loading which depends upon the plan’s difficulty level and the planner’s skills.
In the study that was done in cooperation with Associate Professor Umetani, an algorithm was developed by two teams that will generate a plan using mathematical optimization from a large number of combinations. The potential of the practical use of this technology will be assessed by both the teams. Thus, through digitalization, the services can be improved and the time required to respond to the customer in case of a change in the transport volume or port calls order is also reduced.
The MOL Group takes an active stand to promote the practical use and application of ICT and makes use of the specialized knowledge of each division. The major goal is to make the shipping group the customer’s first choice when it comes to transport and logistics.