Simulated annealing with different vessel assignment strategies for the continuous berth allocation problem

Lin, Shih-Wei; Ting, Ching‐Jung; Wu, Kun-Chih

doi:10.1007/s10696-017-9298-2

Cited by 19 publications

(12 citation statements)

References 46 publications

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“…Mahpour [33] et al analyzed several factors affecting terminal operation and obtained the best time to serve vessels. Lin [34] et al optimized the berth allocation in container terminal by considering the service time and penalty cost.…”

Section: Literature Review and Related Workmentioning

confidence: 99%

Container Terminal Berth and Yard Collaborative Allocation for Import and Export Synchronous Operations by Computational Logistics

Jiang

Lei

2022

Discrete Dynamics in Nature and Society

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Container terminal operators have practical and clear requirements on improving operational efficiency and service level to address running challenges. The resource allocation and collaborative scheduling of quayside berth and storage yard are vital issues in the optimization of container terminal handling systems (CTHSs). The allocation of berth in quayside and blocks on storage yard directly affects the running efficiency of CTHS. Consequently, we focus on the berth and yard collaborative allocation for import and export synchronous operations (BYCA-IESOs) and propose the BYCA-IESO research model based on synchronous or asynchronous integrated scheduling strategy by computational logistics. The BYCA-IESO model is a mixed integer quadratic programming model to minimize multiple time consumption of calling liners and the total horizontal transferring distances of yard trailers at container terminals. Furthermore, we design other two allocation policies for comparison on the BYCA-IESO, which are both multistage scheduling strategy profiles. CPLEX 20.1.0 is applied to implement and solve the model and tactics of BYCA-IESO. Accordingly, the feasibility, validity, and relative merits of the models and strategies are obtained and verified by analyzing and comparing multiple numerical experimental results.

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Section: Literature Review and Related Workmentioning

confidence: 99%

Container Terminal Berth and Yard Collaborative Allocation for Import and Export Synchronous Operations by Computational Logistics

Jiang

Lei

2022

Discrete Dynamics in Nature and Society

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“…2 identifies the set of scheduling problems on a container terminal. From left to right, the first two scheduling problems occur upon arrival of a deep-sea vessel: berth allocation and bay scheduling (Al-Dhaheri and Diabat 2015; Bierwirth and Meisel 2010;Tavakkoli-Moghaddam et al 2009;Kim and Park 2004;Lin et al 2018;Liu et al 2017;Jin et al 2015;Iris et al 2015). Berth allocation is used to determine which ship can berth at which quay in ports having multiple berth sites available.…”

Section: Background and Problem Formulationmentioning

confidence: 99%

“…Jungwattanakit et al (2009) report that SA is superior to GA and Tabu Search for large scale HFS problems. There is successful precedent in using SA for problems in terminal waterside operations (Lin et al 2018).…”

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confidence: 99%

Coordinated optimization of equipment operations in a container terminal

et al. 2019

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Increasing international maritime transport drives the need for efficient container terminals. The speed at which containers can be processed through a terminal is an important performance indicator. In particular, the productivity of the quay cranes (QCs) determines the performance of a container terminal; hence QC scheduling has received considerable attention. This article develops a comprehensive model to represent the waterside operations of a container terminal. Waterside operations comprise single and twinlift handling of containers by QCs, automated guided vehicles and yard cranes. In common practice, an uncoordinated scheduling heuristic is used to dispatch the equipment operating on a terminal. Here, uncoordinated means that the different machines that operate in the container terminal seek optimal productivity solely considering their own respective stage. By contrast, our model provides a coordinated schedule in which operations of all terminal equipment can be considered at once to achieve productivity closer to the QC optimal. The model takes the form of a hybrid flow shop (HFS) with novel features for bi-directional flows and job pairing. The former enables jobs to move freely through the HFS in both directions; the latter constrains certain jobs to be performed simultaneously by a single machine. We solve the coordinated model by means of a tailored simulated annealing (SA) algorithm that balances solution quality and computational time. We empirically study time-bounded variants of SA and compare them with a branchand-bound algorithm. We show that our approach can produce coordinated schedules for a terminal with up to eight QCs in near real time.

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“…They compared their method with other methods in the literature for testing their results. After three years, Lin et al (2018) developed a new version of SA based on different vessel assignment strategies to solve DCBAP. The results presented in this work are considered the best so far.…”

Section: Fig 2 Type Of Terminal Layouts 2 Literature Reviewmentioning

confidence: 99%

A modified sailfish optimizer to solve dynamic berth allocation problem in conventional container terminal

Issam¹,

Lajjam²,

Merouani³

et al. 2019

10.5267/j.ijiec

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During the past two decades, there has been an increase on maritime freight traffic particularly in container flow. Thus, the Berth Allocation Problem (BAP) can be considered among the primary optimization problems encountered in port terminals. In this paper, we address the Dynamic Berth Allocation Problem (DBAP) in a conventional layout terminal which differs from the popular discrete layout terminal in that each berth can serve multiple vessels simultaneously if their total length is equal or less than the berth length. Then, a Modified Sailfish Optimizer (MSFO) meta-heuristic based on hunting sailfish behavior is developed as an alternative for solving this problem. Finally, computational experiments and comparisons are presented to show the efficiency of our method against other methods presented in the literature in one hand. We also discuss the productivity of a container terminal based on different scenarios which can happen.

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Simulated annealing with different vessel assignment strategies for the continuous berth allocation problem

Cited by 19 publications

References 46 publications

Container Terminal Berth and Yard Collaborative Allocation for Import and Export Synchronous Operations by Computational Logistics

Container Terminal Berth and Yard Collaborative Allocation for Import and Export Synchronous Operations by Computational Logistics

Coordinated optimization of equipment operations in a container terminal

A modified sailfish optimizer to solve dynamic berth allocation problem in conventional container terminal

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