A simulation optimization method for vehicles dispatching among multiple container terminals. Issue 7 (1st May 2015)

• Record Type: Journal Article
• Authors: Tao, Jinghui; Qiu, Yuzhuo
• Is Part Of: Expert systems with applications. Volume 42:Issue 7(2015)
• Page Start: 3742
• Page End: 3750
• Publication Date: 2015-05-01
• Subjects: Container terminal -- Online dispatching -- Event-driven simulation -- Evolution algorithm; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2014.12.041
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: An online strategy with reduced empty traveling and global balancing is proposed. A linear evaluation function is established for real-time dispatching empty vehicles. Two berths model is established with ships arriving at different time. Different factors are introduced into the evaluation function by linear combination. Abstract: Container terminals, serving as the hubs between container ships and other transportations nodes, are of extreme importance in streamlining the ever increasing global trade. Many different factors affect the service efficiency in container terminals, which inspire great interest in both industrial and academic researches. This work focuses on vehicle dispatching problem which decides, for each internal vehicle in the port, where to go to find a new loading or unloading task in container terminals after finishing the previous one. A multi-factor online dispatching method, which takes both empty traveling and location balance into consideration, is proposed to fit the current condition of the physical and information infrastructure in most of the ports in mainland China. Such a method is established by using combined evolution searching function and discrete event simulation. Through comparing our dispatching method with the traditional dedicated vehicle dispatching methods in various simulation cases, together with theoretical analysis, we prove that our method delivers substantial efficiency improvement in terms of reducing ship serving time and vehicle empty traveling, regardless of changing environment we have examined in the study.