Real-time schedule recovery in liner shipping service with regular uncertainties and disruption events

Li, Chen; Qi, Xinyuan; Song, Dong‐Ping

doi:10.1016/j.trb.2015.10.004

Cited by 92 publications

(54 citation statements)

References 36 publications

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“…Wang and Meng [18] and Qi and Song [19] highlighted that short segments of a given liner shipping route require more buffer time due to weak flexibility. Li et al [10] focused on a real-time schedule recovery problem for a liner shipping service. Two types of uncertainties in liner shipping operations were defined: (1) regular uncertainties; and (2) disruptive events.…”

Section: Vessel Schedule Recoverymentioning

confidence: 99%

“…The planned arrival time of vessels at port + 1 was set based on the following relationship: +1 = + ℎ + ∀ ∈ (hours). In order to conduct the computational experiments for this study, the data from the liner shipping literature and the MCT operations literature [6][7][8][9][10][11][37][38][39][40][50][51][52][53][54][55] were used to generate the parameter values for the GVSRPL mathematical model. The adopted parameter values are presented in Table 1.…”

Section: Input Data Generationmentioning

confidence: 99%

“…Since the vessels, sailing through ECAs, can use only expensive low-sulfur fuel, energy efficiency becomes a major factor in selecting the appropriate vessel schedule recovery strategy.The effects of disruptions on the planned vessel schedules, the demand for more efficient fuel utilization in liner shipping, and the existing environmental regulations underscore the need for the development of effective green vessel schedule recovery methods, which can be used by liner shipping companies in practice. Although, a few studies have addressed the vessel schedule recovery in liner shipping and proposed a set of mathematical models for the vessel schedule recovery problem [4,[9][10][11], none of the existing studies on vessel schedule recovery have taken into account the liner shipping routes, which pass through ECAs and where additional regulations are imposed by IMO. This study proposes a novel mixed-integer nonlinear programming model for the green vessel schedule recovery problem for the liner shipping route, passing through ECAs.…”

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A Vessel Schedule Recovery Problem at the Liner Shipping Route with Emission Control Areas

et al. 2019

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Liner shipping is a vital component of the world trade. Liner shipping companies usually operate fixed routes and announce their schedules. However, disruptions in sea and/or at ports affect the planned vessel schedules. Moreover, some liner shipping routes pass through the areas, designated by the International Maritime Organization (IMO) as emission control areas (ECAs). IMO imposes restrictions on the type of fuel that can be used by vessels within ECAs. The vessel schedule recovery problem becomes more complex when disruptions occur at such liner shipping routes, as liner shipping companies must comply with the IMO regulations. This study presents a novel mixed-integer nonlinear mathematical model for the green vessel schedule recovery problem, which considers two recovery strategies, including vessel sailing speed adjustment and port skipping. The objective aims to minimize the total profit loss, endured by a given liner shipping company due to disruptions in the planned operations. The nonlinear model is linearized and solved using CPLEX. A number of computational experiments are conducted for the liner shipping route, passing through ECAs. Important managerial insights reveal that the proposed methodology can assist liner shipping companies with efficient vessel schedule recovery, minimize the monetary losses due to disruptions in vessel schedules, and improve energy efficiency as well as environmental sustainability.Energies 2019, 12, 2380 2 of 28 arrival, departure, and waiting times of vessels at ports, sailing speed, and service frequency are planned at the tactical level (i.e., every 3-6 months) [3].However, in practice, many disruptions may occur that will further affect the planned vessel schedules. Some of the disruptions include severe weather, port congestion, mechanical failures, port strikes, and natural hazards. Brouer et al. [4] highlighted piracy and crew strikes on vessels as some of the unusual causes of disruptions in liner shipping. Notteboom [5] found that about 70%-80% of liner shipping routes recorded late arrivals at one or multiple port(s) of call along their routes. The latter affected the planned vessel schedules, and liner shipping companies faced the challenge of recovering the planned vessel schedules. Disruptions in vessel schedules usually result in late arrivals of vessels at the consecutive ports of call. In some cases, the whole network could be affected by the delay at one of the segments of the liner shipping route (which can be a voyage leg or a port). Disruptions in the planned schedule of vessels can significantly increase the total route service cost for the liner shipping company, and, consequently, reduce the desired profit or even result in monetary losses.In the event of a disruption in the planned vessel schedule, the liner shipping company has to decide on the most viable action that could be taken in order to recover the schedule and ensure timely delivery of cargo or at least minimize the cargo delivery delays. If a disruption occurs in sea and/or at ports,...

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Section: Vessel Schedule Recoverymentioning

confidence: 99%

Section: Input Data Generationmentioning

confidence: 99%

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confidence: 99%

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A Vessel Schedule Recovery Problem at the Liner Shipping Route with Emission Control Areas

et al. 2019

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“…Aydin et al (2017) propose a dynamic ship speed optimization model, for determining a liner vessel's optimal sailing speed under fuel cost minimization objectives while considering stochastic port service times and port delay penalties. Li et al (2016) propose a dynamic programming model for regular sea voyage and port delay recovery and occasional disruption event recovery that mainly occur at ports, through the adjustment of the vessel's sailing speed. The optimization criteria involve, the vessel's fuel and operating costs per voyage, and the vessel's delay costs which incorporate the cargo's misconnecting, inventory and rerouting costs, along with the shippers goodwill loss cost.…”

Section: Literature Review: a Critical Taxonomymentioning

confidence: 99%

The impact of slow steaming on the carriers’ and shippers’ costs: The case of a global logistics network

Mallidis

Iakovou

Dekker

et al. 2018

Transportation Research Part E: Logistics and Transportation Re

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We propose an analytical modeling methodology for quantifying the impact of slow steaming on the carrier's voyage cost and on the shipper's total landed logistics costs. The developed methodology can be employed by a carrier and a shipper in their contract negotiations, in order for the two parties to determine how they could divide between them the savings resulted from slow steaming. We demonstrate that the impact of slow steaming and speed adjustment policies on the shippers' total landed logistics costs tend to increase as the vessel travels towards the end of its voyage.

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“…Li et al (2016) studied recovery policies for liner shipping under several regular uncertainties. The study differentiated between two types of uncertainties in liner shipping and proposed different schemes to tackle them.…”

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confidence: 99%

A Holistic Optimization Model for Integrated Tactical Level Planning in Liner Shipping

Pasha¹

2020

Preprint

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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.

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Real-time schedule recovery in liner shipping service with regular uncertainties and disruption events

Cited by 92 publications

References 36 publications

A Vessel Schedule Recovery Problem at the Liner Shipping Route with Emission Control Areas

A Vessel Schedule Recovery Problem at the Liner Shipping Route with Emission Control Areas

The impact of slow steaming on the carriers’ and shippers’ costs: The case of a global logistics network

A Holistic Optimization Model for Integrated Tactical Level Planning in Liner Shipping

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