An epsilon-constraint-based exact multi-objective optimization approach for the ship schedule recovery problem in liner shipping

被引:35
作者
Elmi, Zeinab [1 ]
Li, Bokang [1 ]
Liang, Benbu [2 ,3 ]
Lau, Yui-yip [4 ]
Borowska-Stefanska, Marta [5 ]
Wisniewski, Szymon [5 ,6 ]
Dulebenets, Maxim A. [1 ]
机构
[1] Florida A&M Univ, Florida State Univ, Dept Civil & Environm Engn, FAMU FSU Coll Engn, 2035 E Paul Dirac Dr,Sliger Bldg,Suite 275, Tallahassee, FL 32310 USA
[2] Wuhan Univ Technol, Sch Management, Wuhan 430070, Peoples R China
[3] Delft Univ Technol, Fac Technol Policy & Management, Dept Multiactor Syst, Bldg 31,Jaffalaan 5, NL-2628 BX Delft, Netherlands
[4] Hong Kong Polytech Univ, Coll Profess & Continuing Educ, Div Business & Hospitality Management, Kowloon, 9 Hoi Ting Rd, Hong Kong, Peoples R China
[5] Univ Lodz, Inst Built Environm & Spatial Policy, Fac Geog Sci, Kopcinskiego St 31, PL-90142 Lodz, Poland
[6] Univ Lodz, Res Ctr European Spatial Policy & Local Dev, Kopcinskiego St 31, PL-90142 Lodz, Poland
关键词
Maritime supply chains; Uncertainty; Disruptions; Ship schedule recovery; Multi -objective optimization; Service reliability; DISRUPTION MANAGEMENT; VESSEL; MODEL; DESIGN; SERVICE;
D O I
10.1016/j.cie.2023.109472
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Time management is crucial for liner shipping services. A variety of unexpected events can disrupt liner shipping schedules. A real-time port capacity analysis and rescheduling the original ship operations would be necessary to counteract the negative effects of such disruptions. Different ship schedule recovery options can be adopted in response to disruptive events (e.g., ship sailing speed adjustment, skipping of disrupted ports). However, shipping lines face conflicting decisions when selecting ship schedule recovery options. As an example, the commonly-used ship speeding-up option could effectively reduce delays during the voyage but would increase the fuel cost. Similarly, the skipping of disrupted ports may substantially decrease the associated delays but would incur additional costs associated with supply chain disruptions and misconnected cargo. Nevertheless, there is a lack of analytical methods that enable the evaluation of competing objectives in ship schedule recovery and effective multi-objective solution approaches. Therefore, this study proposes a novel multi-objective model for ship schedule recovery that aims not only to minimize the total late ship arrivals at ports but also to minimize the total profit loss due to disruptive events that may occur at sea and/or at ports. An epsilon-constraint-based exact optimization algorithm is adopted to obtain optimal Pareto Fronts. The computational experiments conducted for a real-life transit route demonstrate that the adopted exact optimization algorithm is able to generate Pareto Fronts in a timely manner. Moreover, the conducted sensitivity analyses provide interesting insights regarding the effects of different disruption types and unit fuel costs on ship schedule recovery.
引用
收藏
页数:21
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