Gunma University, Meiji University, and Japan Pallet Rental Co., Ltd. (JPR) have made a leap forward in the "Collaboration Area Data Sharing / AI System Development Promotion Project for Promoting Connected Industries", a subsidized project publicly solicited by the New Energy and Industrial Technology Development Organization. A joint transportation matching system that aims to improve the efficiency of logistics, "a cross-industry joint transportation matching service that realizes white logistics," was proposed and adopted.
Recently, the logistics industry is calling for a "logistics crisis."More than 7% of the composition of workers by age group related to the transportation industry is in their 40s and 60s (Japan Trucking Association "Current Situation and Issues of Trucking Industry in Japan 2018"), and working hours are 2% longer than all industries. Despite this, the annual income is 1% less (Ministry of Health, Labor and Welfare "Basic Survey on Wage Structure"), and the shortage of truck drivers has become a social issue.
On the other hand, the loading efficiency of trucks is 40% (see "Current Situation Surrounding Logistics" by the Ministry of Land, Infrastructure, Transport and Tourism). it is conceivable that.In addition, in the Comprehensive Logistics Policy Outline (1-2017), which shows the guidelines of the government's logistics and logistics administration, the goal is to improve logistics efficiency through cooperation and collaboration, and from "individual optimization to overall optimization". There is a strong demand for a shift from competition to co-creation.
In order to solve these "logistics crises," JPR, Meiji University, and Gunma University make full use of logistics know-how and AI technology to extract companies with high merits through collaboration and collaboration to create a more efficient logistics network. Aim to develop a "joint transportation matching system" that proposes.
Meiji University has developed a model for transportation cost calculation utilizing the knowledge of Professor Koji Inui, who specializes in mathematical data science in the Faculty of Comprehensive Mathematics. A joint transportation matching system from the standpoint of mathematical optimization and the theory of cooperative games (mathematical theory that discusses the conditions for establishing cooperation by multiple businesses and the fair cost burden at the time of cooperation) with the participation of researchers). Support the development of the core engine (AI) of.
In the future, we will succeed in many matchings with this system and aim to dramatically improve the efficiency of truck transportation. Furthermore, as the globalization of logistics progresses, we believe that the need for matching in joint transportation will increase overseas as well. We also aim to contribute to the efficiency of global logistics through joint transportation matching that is not tied to Japan.
