Multi-objective and prioritized berth allocation in container ports

Cheong, Chun Yew; Tan, Kay Chen; Liu, Dikai; Lin, Chih-Hao

doi:10.1007/s10479-008-0493-0

Cited by 76 publications

(48 citation statements)

References 23 publications

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“…The dynamic hybrid BAP with position-dependent handling times is studied by Imai et al (2007) for indented berths, and Cordeau et al (2005). Draft restrictions in dynamic hybrid BAP are considered by Nishimura et al (2001) and Cheong et al (2010).…”

Section: Hybrid Bapmentioning

confidence: 99%

Exact and heuristic methods to solve the berth allocation problem in bulk ports

Umang

Bierlaire

Vacca

2013

Transportation Research Part E: Logistics and Transportation Re

114

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The Berth Allocation Problem (BAP) is one of the most critical and widely studied problems in port operations. While significant contributions have been made in the use of operations research methods and techniques to solve the BAP in container terminals, almost no attention has been directed to bulk ports. In this paper, we study the berth allocation problem in bulk ports for hybrid berth layout and dynamic vessel arrivals. A key difference that distinguishes the berth allocation problem in bulk ports from that in container terminals is that it is necessary to account for the cargo type on the vessel. In our model, the cargo locations on the yard and the locations of the fixed facilities such as conveyors and pipelines along the quay are explicitly taken into consideration in modeling the handling times of the vessels berthing at the port. The objective of the allocation is to minimize the total service time of all vessels berthing at the port in a given planning horizon. For a given yard layout of the bulk terminal and given locations of fixed facilities such as conveyors and pipelines along the quay, our model enhances coordination between berthing and yard activities. We present a mixed integer linear programming (MILP) approach to model the problem, and an alternate exact solution approach based on generalized set partitioning. A heuristic approach based on the principle of squeaky wheel optimization is also presented. We compare the formulations from a computational perspective through extensive numerical experiments based on instances inspired from real data obtained from SAQR port, Ras Al Khaimah, UAE, the biggest bulk port in the middle east. Our research problem derives from the realistic requirements of the port where currently the waiting times for the vessels are very large. The results indicate that the set partitioning approach and the heuristic approach can be used to obtain near-optimal solutions for even larger problem size.2

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Section: Hybrid Bapmentioning

confidence: 99%

Exact and heuristic methods to solve the berth allocation problem in bulk ports

Umang

Bierlaire

Vacca

2013

Transportation Research Part E: Logistics and Transportation Re

114

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show abstract

“…Lee et al (2010) developed two greedy randomized adaptive search procedures for the BAPC. Cheong et al (2010) dealt with BAPC with multi-objectives of makespan, waiting time and degree of deviation from a predetermined priority schedule. They developed a multi-objective evolutionary algorithm for that problem.…”

Section: Literature Reviewmentioning

confidence: 99%

The strategic berth template problem

Imai

Yamakawa

Huang

2014

Transportation Research Part E: Logistics and Transportation Re

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“…However, this is still an NP-hard single-level multi-objective programming model, so then, an evolutionary algorithm based on individual problems is required. Evolutionary algorithms have been widely used in many multiobjective optimization problems, such as allocation problems [29], scheduling problems [30], and assignment problems [31]. Here, the NSGA-II is applied because of its superior computational capacity.…”

Section: Introductionmentioning

confidence: 99%