Multi-period liner ship fleet planning with dependent uncertain container shipment demand

Abstract

This paper deals with a realistic multi-period liner ship fleet planning problem by incorporating stochastic dependency of the random and period-dependent container shipment demand. This problem is formulated as a multi-period stochastic programming model with a sequence of interrelated two-stage stochastic programming (2SSP) problems characterized ship fleet planning in each single period. A solution method integrating dual decomposition and Lagrangian relaxation method is designed for solving the developed model. Numerical experiments are carried out to assess applicability and performance of the proposed model and solution algorithm. The results further demonstrate importance of stochastic dependence of the uncertain container shipment demand.

A stochastic programming formulation for strategic fleet renewal in shipping

“…However, the proposed model does not take into account uncertainty in the demand forecast. Meng et al (2014) also base their solution method for the fleet planning problem of liner container shipping on a limited number of fleet configurations made by company experts, but include uncertainty in demand as part of the deployment considerations. The demand is assumed to be dependent on that of the previous period.…”

Container Slot Allocation for Time-Sensitive Cargo in Maritime Transportation: A One-Phase Model with consideration of Port Congestion

“…According to Panayides and Song [25] and Wang and Meng [26], the ''time factor" is a fundamental requirement of practical liner shipping networks, in which port congestion plays an important role. Meng and Wang [27], Wang et al [16], Wang and Meng [26], and Meng et al [28] considered transit time to solve the container paths and network design problem. Wang and Meng [29] proposed a mixed-integer nonlinear stochastic model to hedge against uncertain container handling times and port congestion.…”

Empty container movements arising from cargo seasonality: Turkish terminals

“…Chang et al (2008) thought over benefiting 20-foot and 40-foot containers in place of each other. The optimisation studies in the literature extended to locating depot facilities (Dang et al, 2013;Olivo et al, 2013) and container storage areas (Lei and Church, 2011;Mittal et al, 2013) in addition to on board solutions of voyage planning (Christiansen et al, 2013;Braekers et al, 2013;Meng et al, 2015) and empty container allocation (Cheung and Chen, 1998;Song and Dong, 2011;Long et al, 2012). Furthermore, carrier based solutions such as flexible destinations during a voyage (Song and Dong, 2010) and street-turns (Jula et al, 2006;Legros et al, 2016) were discussed.…”