Development of a maritime transportation planning support system for car carriers based on genetic algorithm

  • Authors:

  • Moo Hong Kang;Hyung Rim Choi;Hyun Soo Kim;Byung Joo Park

  • Affiliations:

  • Department of Management, University of Arkansas at Little Rock, Little Rock, USA 72204;Department of Management Information Systems, Dong-A University, Busan, South Korea 602-760;Department of Management Information Systems, Dong-A University, Busan, South Korea 602-760;Gyeongnam Development Institute, Gyeongnam, South Korea 641-060

  • Venue:
  • Applied Intelligence
  • Year:
  • 2012

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Abstract

Recently, the port logistics market is rapidly expanding, along with the active maritime trade. To adjust to this trend and gain a competitive advantage, competition among shipping companies at home and abroad has intensified, and many efforts are being made for the improvement of customer services and cost saving. In particular, car carriers transporting more than 80% of total car import/export volume must quickly make efforts to reduce transportation costs. Much research has been conducted to improve the efficiency of maritime transportation, but studies on car carriers, which are given relatively less importance, have been lacking. The car carrier's transportation planning is similar to the vehicle routing problem, but it is much more complicated in that cars and cargo are prepared at different points in time, and cargo can be loaded not only at the departing port but also at other ports. Therefore, in an effort to solve the problem, this study has developed a meta-heuristic algorithm based on a genetic algorithm, and we have succeeded in developing a maritime transportation planning support system with the algorithm, thus making it possible to prepare various alternatives, evaluate them, and consequently support user's decision making.