Dynamic recovery actions in multi-objective liner shipping service with buffer times

This paper investigates the dynamic recovery policies for liner shipping service with the consideration of buffer time allocation and uncertainties. We aim to allocate the buffer time at the tactical level and then determine the optimal policy, including speed optimization strategy, port skipping and acceleration rate choice, for recovering from disruptions due to various uncertainties or random adverse events, which cause vessel delays. To achieve this, we attempt to obtain the optimal balance among economic, environmental and service-reliable objectives. A novel mathematical formulation is introduced to solve the robust vessel scheduling problem with short- and long-term decisions. Furthermore, we propose and test two heuristics to solve the proposed model. Experiments on the container liner shipping service show the validity of the model and some managerial insights are gained from them.

Fuzzy Scheduling Problem of Vessels in One-Way Waterway

Effective use of port waterways is conducive to enhancing port competitiveness. To minimize the waiting time of ships, improve traffic efficiency, and enhance the applicability of the model to the presence of uncertain factors, a fuzzy scheduling optimization method for ships suitable for one-way waterways is proposed based on fuzzy theory. Considering the ambiguity of the speed of ships entering and exiting the port or the time it takes to cross the channel, the previous research on vessel scheduling on one-way waterways has been extended by introducing a triangular fuzzy number and a method for determining the feasible navigable time window of a ship subject to the tide height constraint was proposed. In this study, the genetic algorithm is used to construct the mathematical model for solving fuzzy vessel scheduling problems based on time optimization, and the minimum delay strategy is used to determine the service sequence. Then, the parameters setting are discussed in detail to find the optimal settings. Finally, an experimental comparative analysis of the randomly generated cases was conducted based on the simulated data. The results show that the designed fuzzy vessel scheduling algorithm reduces the dependence on the port environment, is versatile, and can effectively improve the efficiency of ship schedules and traffic safety compared to other methods. Moreover, it can avoid the problem of the illegal solution occurring in the manual scheduling method.

Vessel Scheduling Optimization Model Based on Variable Speed in a Seaport with One-Way Navigation Channel

To improve the efficiency of in-wharf vessels and out-wharf vessels in seaports, taking into account the characteristics of vessel speeds that are not fixed, a vessel scheduling method with whole voyage constraints is proposed. Based on multi-time constraints, the concept of a minimum safety time interval (MSTI) is clarified to make the mathematical formula more compact and easier to understand. Combining the time window concept, a calculation method for the navigable time window constrained by tidal height and drafts for vessels is proposed. In addition, the nonlinear global constraint problem is converted into a linear problem discretely. With the minimum average waiting time as the goal, the genetic algorithm (GA) is designed to optimize the reformulated vessel scheduling problem (VSP). The scheduling methods under different priorities, such as the first-in-first-out principle, the largest-draft-vessel-first-service principle, and the random service principle are compared and analyzed experimentally with the simulation data. The results indicate that the reformulated and simplified VSP model has a smaller relative error compared with the general priority scheduling rules and is versatile, can effectively improve the efficiency of vessel optimization scheduling, and can ensure traffic safety.

Identification and Prediction of Ship Maneuvering Motion Based on a Gaussian Process with Uncertainty Propagation

Maritime transport plays a vital role in economic development. To establish a vessel scheduling model, accurate ship maneuvering models should be used to optimize the strategy and maximize the economic benefits. The use of nonparametric modeling techniques to identify ship maneuvering systems has attracted considerable attention. The Gaussian process has high precision and strong generalization ability in fitting nonlinear functions and requires less training data, which is suitable for ship dynamic model identification. Compared with other machine learning methods, the most obvious advantage of the Gaussian process is that it can provide the uncertainty of prediction. However, most studies on ship modeling and prediction do not consider the uncertainty propagation in Gaussian processes. In this paper, a moment-matching-based approach is applied to address the problem. The proposed identification scheme for ship maneuvering systems is verified by container ship simulation data and experimental data from the Workshop on Verification and Validation of Ship Maneuvering Simulation Methods (SIMMAN) database. The results indicate that the identified model is accurate and shows good generalization performance. The uncertainty of ship motion prediction is well considered based on the uncertainty propagation technology.

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

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.