Sequencing dual-spreader crane operations: Mathematical formulation and heuristic algorithm

•We introduce a new crane scheduling problem inspired by the unloading of a containership.•The problem is modeled as a mixed-integer linear program.•We develop a procedure for computing a lower bound on the optimal objective value.•A heuristic method is developed for handling large problem instances...

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Veröffentlicht in:European journal of operational research Jg. 262; H. 2; S. 521 - 534
Hauptverfasser: Lashkari, Shabnam, Wu, Yong, Petering, Matthew E.H.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 16.10.2017
Schlagworte:
Container terminal
Dual-spreader crane
Integer programming
OR in the maritime industry
Tandem-lift crane
Integer programming
Dual-spreader crane
Container terminal
OR in the maritime industry
Tandem-lift crane
ISSN:0377-2217, 1872-6860
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Beschreibung
Zusammenfassung:•We introduce a new crane scheduling problem inspired by the unloading of a containership.•The problem is modeled as a mixed-integer linear program.•We develop a procedure for computing a lower bound on the optimal objective value.•A heuristic method is developed for handling large problem instances.•The heuristic produces solutions within 6% of optimal for all instance categories. This paper introduces the problem of scheduling a dual-spreader crane when lifts are subject to a weight limit. A mathematical model is formulated and a fast method for computing a lower bound on the optimal value is proposed. An efficient heuristic approach is designed and subsequently built into a simulated annealing framework to solve the problem. The optimization and heuristic approaches are tested on problem instances of various sizes. The results indicate that the optimization approach produces proven optimal solutions to small-sized instances but fails to solve instances of practical meaning. The heuristic approach can easily match the performance of the optimization approach for small instances and outperforms the optimization approach when tackling larger instances. On average, the heuristic approach produces solutions whose objective values are within 6% of the lower bound.
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2017.03.046