Speed optimizations for liner networks with business constraints

Abstract

In 2018 the International Maritime Organization (IMO) agreed to cut the shipping sector's overall CO2 output by 50% by 2050. One of the key methods in reaching this goal is to improve operations to limit fuel consumption. However, it is difficult to optimize speed for a complete liner shipping network as routes interact with each other, and several business constraints must be respected. This paper presents a unified model for speed optimization of a liner shipping network, satisfying numerous real-life business constraints. The speed optimization is in this research achieved by rescheduling the port call times of a network, thus, the network is not changed. The business constraints are among others related to transit times, port work shifts and emission control areas. Other restrictions are fixed times for canal crossing, speed restrictions in the piracy areas and desire for robust solutions. Vessel sharing agreements and other collaboration between companies must also be included. The modeling of the different restrictions is described in detail and tested on real-life data. The scientific contribution of this paper is threefold: We present a unified model for speed optimization together with numerous business constraints. We present a general framework for handling routes with different frequencies. Moreover, we present a bi-objective model for balancing robustness of schedules against fuel consumption. The tests show that the real-life requirements can be handled by mixed integer programming and that the model finds significant reductions of bunker consumption and cost for large-scale real-life instances.

Bibliometric Review of Route Optimization in Maritime Transportation: Environmental Sustainability and Operational Efficiency

“…Many authors investigated optimum ship speeds for diminishing emissions such as CO 2 , sulfur (SO x ), and other greenhouse gases (75)(76)(77)(78)(79). Reinhardt et al (80) proposed a mathematical model on optimum ship speed to meet the CO 2 target of the International Maritime Organization for 2050. Andersson et al (39) emphasized that fuel prices have a significant role in sailing speed optimization.…”

Bunkering and information decisions in the sea cargo service industry based on uncertain spot price

“…Du et al (2019) propose three viable countermeasures within the framework of an effective two-stage optimization solution to solve the sailing speed and trim optimization problem of ships and thereby minimize ships' fuel consumption. Reinhardt et al (2020) consider several business constraints when studying speed optimization and bunkering. The literature also considers other factors such as terminal allocation (Zhen et al, 2016), uncertain service times and time windows at ports (Aydin et al, 2017), distribution-free stochastic bunker prices (Wang, Meng, & Kuang, 2018), and wind conditions along shipping paths (Medina et al, 2020).…”

Ship Speed Optimization Considering Ocean Currents to Enhance Environmental Sustainability in Maritime Shipping

“…Later, He et al [21] relax this assumption and suggest a consumption function model which is a general continuously differentiable and strictly convex function, but without a concrete form of variable impacts, causing varying costs per unit of distance traveled by the ship. [22], carbon emission Qi and Song [24] Liner Scheduling Speed Uncertain port times De et al [25] Liner Routing & bunkering Speed Port time windows, emission Reinhardt et al [26] Liner Scheduling Speed Schedule robustness Andersson et al [27] RoRo Fleet deployment Speed Xia et al [28] Liner Fleet deployment Speed, payload Du et al [29] Liner Berth allocation Speed Departure delay Venturini et al [30] Liner Berth allocation Speed Carbon emission Yao et al [31] Liner Bunkering Speed Empirical consumption function Kim et al [32] Liner Bunkering Speed Carbon emission Aydin et al [33] Liner Bunkering Speed Extension of [31], port time windows De et al [34] Liner Bunkering Speed Disruption recovery Zhao and Yang [35] Liner Maintenance Speed Dockyard choice…”

“…With its basic function forms, ship speed optimization is incorporated into other ship operation problems at tactical and strategic levels, in order to reveal the direct impact of speed on the transit time and service quality of shipping [21,36]. Typical problems addressed are ship routing and scheduling [22][23][24][25][26], fleet deployment [27,28], berth allocation [29,30], bunker fuel management [31][32][33][34] and maintenance scheduling [35]. Relevant studies are listed in Table 1.…”