Development of the Optimization Models and Solution Algorithms for the Vessel Schedule Recovery Problem in Liner Shipping

Over 80% of the global trade tonnage and 70% of global trade value are carried by oceangoing vessels around the world. However, vessel routing and scheduling is a challenging exercise in liner shipping because of uncertainties that may affect the planned operations. Delays caused by uncertainties, such as weather, natural hazards, labor strikes, and others, increase the complexity of liner shipping, related to schedule adherence and reliability of service. In the event of a delay, liner shipping companies take decisions to recover the schedule, aiming to deliver cargoes in a timely manner. Vessel operators may decide to increase the sailing speed of the ship, which will further increase bunker fuel consumption and the total operational cost of liner shipping operations. The vessel schedule recovery problem becomes even more difficult if the delay is large. The contributions of this dissertation to the state-of-the-art are as follows: 1) a set of operational-level vessel schedule recovery models in liner shipping; 2) the vessel schedule recovery models for the liner shipping routes that pass through Emission Control Areas; 3) consideration of multiple vessel schedule recovery alternatives (e.g., port skipping with and without cargo diversion, speed adjustment, handling rate adjustment); 4) application of the appropriate solution approaches for solving the vessel schedule recovery problem; 5) identification of the key factors that may influence vessel schedule recovery; and 6) presentation of the managerial insights and benefits of the developed vessel schedule recovery optimization models.

Flight Schedule Recovery: A Simulation-Based Approach

In this paper, we report our work on the flight recovery problem for China Eastern Airlines. Traditionally, the flight recovery problem is often modeled as an integer or mixed integer linear programming problem. However, such a model cannot take many complex constraints and uncertainties in real applications. Furthermore, we have found solutions obtained based on such a model difficult to implement in their existing operations, as in the case of CEA. Therefore, we propose a simulation-based approach, which works well with their existing operations. Our work demonstrates the potentials of simulation based methods in the study of the flight recovery problem, and possibly other similar problems.

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

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.