Details

Autor(en) / Beteiligte

• Liu, Zhao
• Liu, Jingxian
• Zhou, Feng
• Liu, Ryan Wen
• Xiong, Naixue

Titel

A Robust GA/PSO-Hybrid Algorithm in Intelligent Shipping Route Planning Systems for Maritime Traffic Networks

Ist Teil von

• Wangji Wanglu Jishu Xuekan = Journal of Internet Technology, 2018-11, Vol.19 (6), p.1635-1644

Ort / Verlag

台灣: 台灣學術網路管理委員會

Erscheinungsjahr

2018

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• The development of intelligent shipping route planning systems is important for maritime traffic networks, and has attracted considerable attention in the field of marine traffic engineering. In practical applications, the traditional experience-based planning scheme has been widely used due to its simplicity and easy implementations. However, the traditional manual procedure is experiencedependent and time-consuming, which may easily lead to unstable shipping route planning in different waters. The purpose of this study automatically and robustly determines that the optimal shipping route is based on artificial intelligence approaches. It is general that Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are almost the most popular methods in route planning. These two heuristic-based optimization techniques benefit from their specific advantages when solving different optimization problems. In this paper, we proposed a hybrid heuristic scheme by integrating GA and PSO to improve the accuracy and ro