Models on ship scheduling in transshipment hubs with considering bunker cost

Zhen, Lu; Shen, Tao; Wang, Shuaian; Yu, Seung Min

doi:10.1016/j.ijpe.2015.12.008

Cited by 41 publications

(13 citation statements)

References 40 publications

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“…On the contrary, if the solution does not satisfy constraints (6) to (8), any combinations with deductions of any tunnel safety provisions (e.g., ⇀ = (1, 0, 0), ⇀ = (0, 0, 1, 0), and ⇀ = (0, 0, 0, 1)) will also be unacceptable according to the safety target. Similar ideas of domination have been applied by other research in operational research (e.g., [12][13][14][15][16][17]) Two domination rules are illustrated as follows.…”

Section: 2mentioning

confidence: 96%

Optimal Allocation of Tunnel Safety Provisions Based on a Quantitative Risk Assessment Model

2016

Scientific Programming

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This paper addresses the issue of optimally selecting the tunnel safety provisions. Tunnel safety provisions are the assets of urban road tunnels which are installed and implemented to reduce the tunnel risks, which are basically selected by expert judgment in practice. An optimization model is proposed to obtain the optimal solution for the selection of tunnel safety provisions. The objective function is to minimize the life cycle costs of tunnel safety provisions, which is subject to the requirements for tunnel safety provisions and the safety targets. Finally, by taking advantage of the special structure of the optimization model, a Bi-Section Search and Bound Algorithm (BSSBA) is designed to efficiently solve the problem.

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Section: 2mentioning

confidence: 96%

Optimal Allocation of Tunnel Safety Provisions Based on a Quantitative Risk Assessment Model

2016

Scientific Programming

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“…A number of researchers have concentrated on the basic vessel scheduling decisions, which include sailing speed at each voyage leg, arrival time, waiting time, handling time, and departure time at each port of call (Chen et al, 2007;Zhen et al, 2016;Dulebenets and Ozguven, 2017;Dulebenets, 2018b;Wang et al, 2019). Zhen et al (2016) estimated arrival times and dwell times at ports of call, including transshipment hubs. Wang et al (2019) developed a tailored branch-and-cut algorithm to solve a mixed-integer programming model that aimed to facilitate intercontinental liner shipping.…”

Section: Vessel Schedule Designmentioning

confidence: 99%

Holistic tactical-level planning in liner shipping: an exact optimization approach

et al. 2020

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Effective liner shipping is important for the global seaborne trade. The volume of cargoes transported by liner shipping has been increasing over the past decades. Liner shipping companies face three levels of decision problems, including strategic, tactical, and operational problems. The tactical-level decisions are commonly made every three to 6 months. These decisions include: (1) port service frequency determination; (2) fleet deployment; (3) sailing speed optimization; and (4) vessel schedule design. Most of the concurrent liner shipping studies have addressed the tactical-level decision problems separately. Even though a few studies have proposed joint planning models that capture multiple decision problems at the same time, none of the conducted studies has integrated all the four tactical-level decision problems. To address this gap in the state-of-the-art, this study presents a holistic optimization model that addresses all the tactical-level liner shipping decision problems, aiming to maximize the total profit obtained from liner shipping services. The key route service cost components, found in the liner shipping literature, are considered in this study, which include: (1) vessel operational cost; (2) vessel chartering cost; (3) port handling cost; (4) port late arrival cost; (5) fuel consumption cost; (6) container inventory costs in sea and at ports of call; and (7) emission costs in sea and at ports of call. An exact optimization approach is adopted for the developed mathematical model. The computational experiments, conducted for a set of Asia-North America liner shipping routes, showcase the efficiency of the proposed approach and offer some important managerial insights.

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“…Landside problems are mainly yard storage area planning and allocation [20][21][22][23][24]. There are also studies considering both container terminal operations planning and vessel scheduling [25][26][27]. None of the above studies related to container terminal operations has investigated the problem of repacking TEUs into FEUs.…”

Section: Literature Review Objectivesmentioning

confidence: 99%

Optimal Container Routing in Liner Shipping Networks Considering Repacking 20 ft Containers into 40 ft Containers

Wang

et al. 2017

Journal of Advanced Transportation

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The volume of a 40 ft container is twice as large as that of a 20 ft container. However, the handling cost (loading, unloading, and transshipment) of a 40 ft container is much lower than twice the corresponding handling cost of two 20 ft containers. Enlightened by this observation, we propose a novel container routing with repacking problem in liner shipping, where two 20 ft containers can be repacked to a 40 ft container in order to reduce the handling cost. We develop a mixed-integer linear programming model that formulates the routing decisions and the repacking decisions in a holistic manner. An illustrative example is reported to demonstrate the applicability of the model. Results show that the benefit of repacking is the most significant when containers are transshipped several times.

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Models on ship scheduling in transshipment hubs with considering bunker cost

Cited by 41 publications

References 40 publications

Optimal Allocation of Tunnel Safety Provisions Based on a Quantitative Risk Assessment Model

Optimal Allocation of Tunnel Safety Provisions Based on a Quantitative Risk Assessment Model

Holistic tactical-level planning in liner shipping: an exact optimization approach

Optimal Container Routing in Liner Shipping Networks Considering Repacking 20 ft Containers into 40 ft Containers

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