Abstract: Described herein relates to a system of and method for optimizing schedule design, via facilitation of agreements, such as environmentally sustainable and/or multi-objective collaborative agreements, between at least one shipping vessel and at least one terminal operator. The present disclosure may include at least one multi-objective mathematical model to capture the proposed collaborative agreements. The first objective of the model may minimize the cost components that are mostly driven by the economic perspectives, while the second objective may minimize emission release components driven by the environmental perspectives. The present disclosure comprises a new multi-objective optimization method comprising the features of the ?-constraint model method and the goal-programming model method. In addition, the present disclosure may facilitate am analysis of trade-offs amongst the economic and environmental perspectives in the ship schedule design.

Abstract: The practical application of a multi-objective mixed integer nonlinear optimization model for the improvement of vessel scheduling, which accounts for all major route service cost components reported in the literature and separates them in two conflicting groups. The original mixed integer nonlinear model is linearized by discretizing the vessel sailing speed reciprocal, and the Global Multi-Objective Optimization Algorithm is developed to solve the linearized model. It was found that negotiation of both vessel service time windows and handling rates between liner shipping companies and marine container terminal operators may significantly reduce the total route service cost components. Furthermore, the numerical experiments show that vessel schedules are more sensitive to the unit fuel cost as compared to the unit carbon dioxide emission cost.

Abstract: A methodology and/or system to automatically generate an optimal collaborative agreement, according to which multiple vessel arrival time windows, start and end times for each time window, and multiple handling rates during each time window are offered by the marine container terminal operator to the liner shipping company at each port of the given liner shipping route. The vessel scheduling problem is formulated as a mixed integer nonlinear programming model, where the total liner shipping route service cost is minimized. A set of linearization techniques are applied to the original model, and the linearized model is solved using CPLEX. A number of computational experiments were performed for the Pacific Atlantic 1 liner shipping route, served by the NYK liner shipping company, with results showing effectiveness of the proposed collaborative agreement and the adopted solution methodology to improve liner shipping operations.

Abstract: A methodology and/or system to automatically generate an optimal collaborative agreement, according to which multiple vessel arrival time windows, start and end times for each time window, and multiple handling rates during each time window are offered by the marine container terminal operator to the liner shipping company at each port of the given liner shipping route. The vessel scheduling problem is formulated as a mixed integer nonlinear programming model, where the total liner shipping route service cost is minimized. A set of linearization techniques are applied to the original model, and the linearized model is solved using CPLEX. A number of computational experiments were performed for the Pacific Atlantic 1 liner shipping route, served by the NYK liner shipping company, with results showing effectiveness of the proposed collaborative agreement and the adopted solution methodology to improve liner shipping operations.

Abstract: The practical application of a multi-objective mixed integer nonlinear optimization model for the improvement of vessel scheduling, which accounts for all major route service cost components reported in the literature and separates them in two conflicting groups. The original mixed integer nonlinear model is linearized by discretizing the vessel sailing speed reciprocal, and the Global Multi-Objective Optimization Algorithm is developed to solve the linearized model. It was found that negotiation of both vessel service time windows and handling rates between liner shipping companies and marine container terminal operators may significantly reduce the total route service cost components. Furthermore, the numerical experiments show that vessel schedules are more sensitive to the unit fuel cost as compared to the unit carbon dioxide emission cost.