Efficient and effective berth allocation is essential to guarantee high container
throughput in a container terminal. Modern mega-terminals are usually comprised of
multiple disjointed berths. However, this type of Berth Allocation Problem (BAP) has
not attracted a lot of attention from the academic world due to its great complexity.
This research develops new methodologies for solving complex BAPs, in particular,
BAPs involving quay crane scheduling in a multiple-berth environment.
This research develops a mathematical model and a new Branch and Price
algorithm (B&P) which hybridizes the column generation approach and the Branch
and Bound method (B&B) to generate optimal multiple-berth plans (MBAP) within
acceptable time limits. A new exact algorithm based on the label-correcting concept is
designed to obtain all potential columns by defining a new label structure and
dominance rules. To accelerate the generation of columns, two heuristics are proposed
to distribute vessels among berths and to establish the handling sequence of the
vessels allocated to each berth. An early termination condition is also developed to
avoid the “tailing off effect” phenomenon during column generation process. The
effectiveness and robustness of the proposed methodology are demonstrated by
solving a set of randomly generated test problems.
Since the Berth Allocation Problem (BAP) and the Quay Crane Scheduling
Problem (QCSP) strongly interact, this research also studies the Simultaneous Berth Allocation and Quay Crane Scheduling Problem (BAQCSP). An advanced
mathematical model and a new hybrid meta-heuristic GA-TS algorithm which is
based on the concept of Genetic Algorithm (GA) are developed to solve the proposed
BAQCSP effectively and efficiently. A new crossover operation inspired by the
memory-based strategy of Tabu Search (TS) and the mutation operation are
implemented to avoid premature convergence of the optimization process. The local
search ability of TS is incorporated into the mutation operation to improve the
exploitation of the solution space. Comparative experiments are also conducted to
show the superiority of the performance of the proposed GA-TS Algorithm over the
B&B and the canonical GA.
Furthermore, this research extends the scope of BAQCSP to consider the
Simultaneous Multiple-berth Allocation and Quay Crane Scheduling Problem
(MBAQCSP). A MBAQCSP model is developed consisting of various operational
constraints arising from a wide range of practical applications. Since MBAQCSP
combines the structures of both MBAP and BAQCSP, the exact B&P proposed for
solving MBAP can be modified to optimally solve MBAQCSP. However, the
calculation time of B&P increases significantly as the V/B ratio (i.e., vessel number to
berth number) grows. In order to eliminate this shortcoming, this research develops a
GA-TS Aided Column Generation Algorithm which hybridizes the GA-TS Algorithm
proposed for solving BAQCSP with the Column Generation Algorithm to locate the
optimal or near optimal solutions of MBAQCSP. The computational results show that
the proposed hybrid algorithm locates excellent near optimal solutions to all test
problems within acceptable time limits, even problems with high V/B ratios. Finally,
this research also shows that the proposed GA-TS Aided Column Generation
Algorithm can be easily modified to solve MBAP efficiently. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy
| Identifer | oai:union.ndltd.org:HKU/oai:hub.hku.hk:10722/167232 |
| Date | January 2012 |
| Creators | Sun, Di, 孙镝 |
| Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
| Source Sets | Hong Kong University Theses |
| Language | English |
| Detected Language | English |
| Type | PG_Thesis |
| Source | http://hub.hku.hk/bib/B48199564 |
| Rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works., Creative Commons: Attribution 3.0 Hong Kong License |
| Relation | HKU Theses Online (HKUTO) |
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