Liner Shipping Service Planning Under Sulfur Emission Regulations

Author(s):  
Shuaian Wang ◽  
Dan Zhuge ◽  
Lu Zhen ◽  
Chung-Yee Lee

Air emissions from ships have become an important issue in sustainable shipping because of the low quality of the marine fuel consumed by ships. To reduce sulfur emissions from shipping, the International Maritime Organization has established emission control areas (ECAs) where ships must use low-sulfur fuel with at most 0.1% sulfur or take equivalent emission-reduction measures. The use of low-sulfur fuel increases the costs for liner shipping companies and affects their operations management. This study addresses a holistic liner shipping service planning problem that integrates fleet deployment, schedule design, and sailing path and speed optimization, considering the effect of ECAs. We propose a nesting algorithmic framework to address this new and challenging problem. Semianalytical solutions are derived for the sailing path and speed optimization problem, which are used in the schedule design. A tailored algorithm is applied to solve schedule design problems, and the solutions are used in fleet deployment. The fleet deployment problem is then addressed by a dynamic programming-based pseudo-polynomial time algorithm. Numerical experiments demonstrate that considering the effect of ECAs in liner shipping operations management can reduce over 2% of the costs, which is significant considering that the annual operating cost of a shipping company’s network can be as high as several billion dollars.

2015 ◽  
Vol 49 (4) ◽  
pp. 922-938 ◽  
Author(s):  
Jun Xia ◽  
Kevin X. Li ◽  
Hong Ma ◽  
Zhou Xu

2019 ◽  
Vol 11 (14) ◽  
pp. 3871 ◽  
Author(s):  
Ming Liu ◽  
Xin Liu ◽  
Maoran Zhu ◽  
Feifeng Zheng

Drone delivery has a great potential to change the traditional parcel delivery service in consideration of cost reduction, resource conservation, and environmental protection. This paper introduces a novel drone fleet deployment and planning problem with uncertain delivery demand, where the delivery routes are fixed and couriers work in collaboration with drones to deliver surplus parcels with a relatively higher labor cost. The problem involves the following two-stage decision process: (i) The first stage determines the drone fleet deployment (i.e., the numbers and types of drones) and the drone delivery service module (i.e., the time segment between two consecutive departures) on a tactical level, and (ii) the second stage decides the numbers of parcels delivered by drones and couriers on an operational level. The purpose is to minimize the total cost, including (i) drone deployment and operating cost and (ii) expected labor cost. For the problem, a two-stage stochastic programming formulation is proposed. A classic sample average approximation method is first applied. To achieve computational efficiency, a hybrid genetic algorithm is further developed. The computational results show the efficiency of the proposed approaches.


2020 ◽  
Author(s):  
Junayed Pasha

Supply chain management plays an important role in ensuring an efficient merchandise trade. Freight transportation is an integral part of supply chain management. A significant part of freight transportation is covered by maritime transportation, as the largest portion of the global merchandise trade, in terms of volume, is carried out by maritime transportation. Liner shipping, which runs on fixed routes and schedules, plays a colossal role for the global seaborne trade. Liner shipping companies deal with three decision levels, namely strategic level, tactical level, and operational level. The strategic-level decisions are taken for more than six months to several years. The tactical-level decisions are effective for three months to six months. Moreover, the operational level decisions are taken for a couple of weeks to less than three months.This dissertation involves the tactical-level decisions in liner shipping, which include: (1) service frequency determination; (2) fleet deployment; (3) sailing speed optimization; and (4) vessel scheduling. The service frequency determination problem deals with determining the time headway between consecutive vessels along a liner shipping route. The fleet deployment problem assigns vessels from the liner shipping company’s fleet (and sometimes, from other liner shipping companies’ fleets) to liner shipping routes. The sailing speed optimization problem deals with selecting sailing speeds along different voyage legs of a given port rotation. The vessel scheduling problem lists the schedules (e.g., arrival time, handling time, departure time) at different ports.A comprehensive review of the liner shipping literature revealed that the existing literature on the tactical-level decisions focused on these problems individually. Solutions from different solution methodologies for the separate problems may have compatibility problems. Moreover, they are not attractive to the liner shipping companies, who look for integrated solutions. Hence, this research aimed to develop a combined mathematical model that comprises the four tactical-level decisions in liner shipping (i.e., service frequency determination, fleet deployment, sailing speed optimization, and vessel scheduling). This mathematical model is named the Holistic Optimization Model for Tactical-Level Planning in Liner Shipping (HOMTLP).The objective of the HOMTLP mathematical model is to maximize of the total profit from transport of cargo. The major route service cost components, found from the literature, are covered by the model, which include: (I) total late arrival cost; (II) total port handling cost; (III) total fuel consumption cost; (IV) total vessel operational cost; (V) total vessel chartering cost; (VI) total container inventory cost in sea; (VII) total container inventory cost at ports of call; (VIII) total emission cost in sea; and (IX) total emission cost at ports of call. Along with the integration of all four tactical-level decisions, the mathematical model has a number of key advantages. First, the model provides flexibility to both the liner shipping company and the marine container terminal operators, as it offers multiple time windows and handling rates at each port of call. Second, the payload carried by the vessels is considered while estimating fuel consumption. Third, the preference of customers is reflected by modification of the container demand at different sailing speeds. Fourth, container inventory is accounted for at ports of call and in sea. Fifth, emissions of different harmful substances are captured in order to preserve the environment.This dissertation carried out a set of numerical experiments to test the performance of the HOMTLP model, where BARON was used as the solution approach. It was revealed that when there was an increase in the unit fuel cost, the unit emission cost, vessel availability, the unit late arrival cost, and the unit freight rate, the sailing speed was reduced. On the other hand, when there was an increase in the unit inventory cost, the unit operational cost, as well as the unit chartering cost, the sailing speed was increased. Moreover, the total required number of vessels was increased, when there as an increase in the unit fuel cost, the unit emission cost, vessel availability, the unit late arrival cost, and the unit freight rate. On the contrary, the total required number of vessels was decreased, when there was an increase in the unit inventory cost, the unit operational cost as well as the unit chartering cost. It was also revealed that the total profit was increased, when more choices were available for time windows and/or container handling rates. The numerical experiments highlighted several other findings. Most importantly, it was found that the HOMTLP model can provide effective tactical-level decisions. Hence, the mathematical model can assist liner shipping companies to take tactical-level decisions, which are effective and profitable.


Author(s):  
Feifeng Zheng ◽  
Zhaojie Wang ◽  
E. Zhang ◽  
Ming Liu

This work investigates the problem of vessel fleet deployment for liner shipping. The objective is to minimize the total cost, i.e., the sum of vessel chartering cost and vessel-route operating cost. In the considered problem, the shipment demand for each route is uncertain and its distribution is unknown. Due to lacking historical data, we use the moment-based ambiguity set to characterize the unknown distributions of demands. We then introduce a distributionally robust model and propose a new approximation approach to solve this problem. Finally, numerical experiments are conducted to demonstrate the performance of our approximation approach.


2015 ◽  
Vol 55 ◽  
pp. 233-240 ◽  
Author(s):  
Henrik Andersson ◽  
Kjetil Fagerholt ◽  
Kirsti Hobbesland

2009 ◽  
Vol 36 (5) ◽  
pp. 397-409 ◽  
Author(s):  
Kjetil Fagerholt ◽  
Trond A. V. Johnsen ◽  
Haakon Lindstad

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2283
Author(s):  
Atif Naveed Khan ◽  
Kashif Imran ◽  
Muhammad Nadeem ◽  
Anamitra Pal ◽  
Abraiz Khattak ◽  
...  

Flexible AC Transmission Systems (FACTS) are essential devices used for the efficient performance of modern power systems and many developing countries lack these devices. Due to the non-existence of these advanced technologies, the national grid remains weak and vulnerable to power stability issues that can jeopardize system stability. This study proposes novel research to solve issues of an evolving national grid through the installation of FACTS devices. FACTS devices play a crucial role in minimizing active power losses while managing reactive power flows to keep the voltages within their respective limits. Due to the high costs of FACTS, optimization must be done to discover optimal locations as well as ratings of these devices. However, due to the nonlinearity, it is a challenging task to find the optimal locations and appropriate sizes of these devices. Shunt VARs Compensators (SVCs) and Thyristor-Controlled Series Compensators (TCSCs) are the two FACTS devices considered for the study. Optimal locations for SVCs and TCSCs are determined by Voltage Collapse Proximity Index (VCPI) and Line Stability Index (Lmn), respectively. Particle Swarm Optimization (PSO) is employed to find the ideal rating for FACTS devices to minimize the system operating cost (cost due to active power loss and capital cost of FACTS devices). This technique is applied to IEEE (14 and 30) bus systems. Moreover, reliable operation of the electricity grid through the placement of FACTS for developing countries has also been analysed; Pakistan being a developing country has been selected as a case study. The planning problem has been solved for the present as well as for the forecasted power system. Consequently, in the current national network, 6.21% and 6.71% reduction in active and reactive power losses have been observed, respectively. Moreover, voltage profiles have been improved significantly. A detailed financial analysis covering the calculation of Operation Cost (OC) of the national grid before and after the placement of FACTS devices is carried out.


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