Fleet routing and scheduling problem based on constraints of chance

Guan, Feng; Peng, Zixuan; Chen, Chao; Guo, Zeng-Yuan; Yu, Shaoqiang

doi:10.1177/1687814017743026

Cited by 7 publications

(4 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…particular aspects [12][13][14][15][16][17]. The planning of tramp vessels' operations presents optimization models and methods.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Efficiency of Tramp Fleet Operating Under the Contracts of Affreightment

KOSKINA,

ONYSHENKO,

DROZHZHYN

et al. 2023

SJSUT.ST

View full text Add to dashboard Cite

The paper considers the vessels operating on carriages of bulk cargoes to get the maximum profit for the shipowner as his main goal. The items in search are the long-term contracts of affreightment with some clauses indicated as indeterminate values, that can be described using a range of values. It leads to a range of voyage indicators. The vessels’ deployment for getting the maximum profit depends on the market situation that is to say possible changes in vessels' time-charter rates and freight rates. This paper presents the mathematical model, based on the fleet and volumes of carriages under a set of contracts of affreightment during the due time. It includes the necessity for the commitment fulfilment by owned and time-chartered vessels and takes into account possible changes in freight rates for cargoes carriages. The presented numerical example demonstrates the opportunity for practical implementation of the model.

show abstract

“…particular aspects [12][13][14][15][16][17]. The planning of tramp vessels' operations presents optimization models and methods.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Efficiency of Tramp Fleet Operating Under the Contracts of Affreightment

KOSKINA,

ONYSHENKO,

DROZHZHYN

et al. 2023

SJSUT.ST

View full text Add to dashboard Cite

show abstract

“…They used particle swarm optimization with composite particles to solve the problem. Guan et al [20] presented a fleet routing and scheduling problem with uncertain time window constraints. They solved the problem using the column generation optimization technique.…”

Section: Ship Routing and Scheduling Problemsmentioning

confidence: 99%

A Set Covering Model for a Green Ship Routing and Scheduling Problem with Berth Time-Window Constraints for Use in the Bulk Cargo Industry

Maneengam

Udomsakdigool

2021

Applied Sciences

View full text Add to dashboard Cite

This paper presents a set covering model based on route representation to solve the green ship routing and scheduling problem (GSRSP) with berth time-window constraints for multiple bulk ports. A bi-objective set covering model is constructed with features based on the minimization of the total CO2 equivalent emissions and the total travel time subject to a limited number of berths in each port, berthing time windows, and the time window for each job. The solutions are obtained using the ε-constraint method, after which a Pareto frontier is plotted. This problem is motivated by the operations of feeder barges and terminals, where the logistics control tower is used to coordinate the routing and berthing time of its barges. We show that the proposed method outperforms the weighted sum method in terms of the number of Pareto solutions and the value of the hypervolume indicator.

show abstract

“…In the third category, Guan et al (2017) designed a linear programming model with chance constraints for the time window of loading cargo. Before the optimization, a survey for the waiting time of ships for berths is carried out in some of the ports with large export volume.…”

Section: Review Of the Literaturementioning

confidence: 99%

Shipping optimization systems (SOS) for tramp: stochastic cargo soft time windows

Noshokaty¹

2021

J. shipp. trd.

View full text Add to dashboard Cite

Cargo time windows have been discussed in the shipping literature in several ways and within several contexts. One way considers the hard time windows, where a fixed date is assigned to both the open and close laycan for the cargo loading and discharging ports. According to this way, the cargo is rejected if the ship cannot meet these time windows. Another way develops soft time windows, where the ship for an additional cost or a penalty may violate the cargo laycan. The context in the previous ways includes a tramp deterministic model. In this paper, the soft time windows are considered within a context of a tramp stochastic model, where both the cargo transport demand and the laycan dates are random variables. The objective is a gross-profit-per-day accompanied with realistic shipping elements embedded into decision support systems known as shipping optimization systems (SOS). The chance-constraint programming and the modified version of the Dantzig–Wolfe decomposition principle known as block-angular linear ratio programming solve the problem. A case study demonstrates that using stochastic soft time windows with stochastic cargo transport demand has considerably improved the gross profit-per-day better than trying to arrive on time by varying ship speed or being within a non-stochastic shipping context.

show abstract

Fleet routing and scheduling problem based on constraints of chance

Cited by 7 publications

References 44 publications

Efficiency of Tramp Fleet Operating Under the Contracts of Affreightment

Efficiency of Tramp Fleet Operating Under the Contracts of Affreightment

A Set Covering Model for a Green Ship Routing and Scheduling Problem with Berth Time-Window Constraints for Use in the Bulk Cargo Industry

Shipping optimization systems (SOS) for tramp: stochastic cargo soft time windows

Contact Info

Product

Resources

About