###### Abstract
(2013) [13] analyzed terminal operations and detected system bottlenecks to highlight possible improvements. A simulation-based optimization approach by [PERSON] et al. (2014) [14] identified that tugboat deficiency contributed to increased waiting times for vessels, and low tugboat utilization had economic consequences. [PERSON] et al. (2014) [15] adopted a simulation-based approach to evaluate the primary supply process of maritime transport carrying crude oil. They highlighted that reducing inventory variance impacted the system operations positively and provided economic benefits by reducing costs. Recently, [PERSON] et al. (2018) [16] used a simulation approach for congestion avoidance in waterways to operate with shorter waiting times and higher throughput by applying the Fisher pairwise comparison method. Mathematical programming is another primary approach used to address vessel shipping operations. [PERSON] et al. (2004) [17] addressed uncertainties in operations and economic costs in the petrochemical sector using a two-stage stochastic optimization approach. [PERSON] et al. (2009) [18] formulated a mixed-integer linear programming (MILP) model to determine the unloading and loading times of crude oil at a port and developed a few valid inequalities to solve the problem effectively. The two-stage stochastic model in [19] addressed the optimization of investment planning for the distribution of petroleum products under uncertainty, providing a specific case study in northern Brazil. Further, the optimization model in [20] addressed ship routing and scheduling problems in crude oil transportation with split deliveries. [PERSON] et al. (2014) [21] formulated an MILP model for multi-echelon container supply-chain networks to minimize the total supply-chain service costs. [PERSON] et al. (2015) [22] designed a downstream segment for a supply chain system in the petroleum industry. Their developed optimization model coupled with a simulation model prescribed the optimal locations of facilities and their capacities. [PERSON] et al. (2017) [23] formulated two MILP models for a scheduling problem to transport refined oil products using tramp ships. [PERSON] et al. (2017) [24] adopted a dynamic programming approach to address the speed optimization problem in liner shipping. Recently, [PERSON] et al. (2019, a) [25] presented a MILP model for integrated scheduling of vessel dispatching and port operations for the closed-loop shipping system in the context of deterministic parameters with a constant travel speed. Few studies addressed the closed-loop container shipping system with uncertainty. To the best of our knowledge, only [PERSON] et al. (2019) [26] handled the closed-loop container shipping system with uncertainty using simulation. They considered the uncertain round-trip time incurred by uncontrollable, unexpected events at destination ports. Using a fixed number of vessels, they examined the opportunity for cost savings by adjusting vessel operation policies. The number of vessels and their voyage speed are vital factors and may have a trade-off for system performance. Considering additional existing uncertainties such as bad weather may generate more reliable and realistic estimates. Therefore, this study extends to the work of [PERSON] et al. (2019) by incorporating new decision factors for the numbers of each type of vessel and forward and backward travel speeds into the simulation model. We also consider additional uncertainties from high wind and low visibility to model the uncertain voyage interruption in the system. Hence, the first objective of this study is to develop a detailed and realistic simulation model for the closed-loop vessel dispatching problem to transport petrochemicals with several uncertainties caused by bad weather and uncontrollable events at destination ports. The second objective is to devise the best vessel operational policies to reduce operating costs in an environmentally friendly manner, considering the different number of vessels and various travel speeds.