Recent Progress Using Matheuristics for Strategic Maritime Inventory Routing

Papageorgiou, Dimitri J.; Cheon, Myun-Seok; Harwood, Stuart M.; Trespalacios, Francisco; Nemhauser, George L.

doi:10.1007/978-3-319-61801-2_3

Cited by 14 publications

(13 citation statements)

References 45 publications

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“…As pointed out in [5], one of the challenges for LNG-ADP problem is the problem size, which is mainly due to the long planning horizon. A common attempt to reduce problem size has been to shorten the planning horizon and then solve consecutive problems in a rolling horizon framework until a feasible solution for the entire planning horizon is available, see e.g., [6,7,22].…”

Section: Solution Methodsmentioning

confidence: 99%

Planning Annual LNG Deliveries with Transshipment

Schütz

2020

Energies

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The introduction of transshipment ports in the liquefied natural gas (LNG) supply chain in recent years offers additional flexibility, but also challenges to the planning of the annual delivery program. We present a new variant of the LNG-annual delivery program (ADP) planning problem by considering transshipment as well as time-dependent sailing times. We present a continuous time formulation for the LNG-ADP problem and propose a rolling horizon heuristic to solve the problem. Both the model and heuristic were used to solve a case inspired by the Yamal LNG project. The computational results show that the heuristic provides good solutions within a relatively short amount of time, especially compared to the exact solution methods. However, there is a trade-off between computational time and solution quality when designing the rolling horizon heuristic. The results also show the impact storage capacity at the transshipment port has on the total cost.

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Section: Solution Methodsmentioning

confidence: 99%

Planning Annual LNG Deliveries with Transshipment

Schütz

2020

Energies

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“…Diz et al [7] developed relax-and-fix and fix-and-optimize heuristics to deal with a real problem related to the Brazilian offshore oil industry. Papageorgiou et al [12] presented an extensive computational study, comparing variants of rolling horizon heuristics, K-opt heuristics, local branching, solution polishing, and hybrid approaches to solve a MIRP. Munguía et al [11] developed a hybrid approach using MILP formulations to solve sub-problems iteratively.…”

Section: Literature Reviewmentioning

confidence: 99%

A Hybrid VNS for the Multi-product Maritime Inventory Routing Problem

Sanghikian

Martinelli

Abu-Marrul

2021

Variable Neighborhood Search

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In a growth scenario of the world economy, it is essential to increase the integration between the different actors in the companies' supply chain, reducing operational costs, and improving efficiency. Ship routing is a crucial part of this integration regarding global maritime commerce. In this work, we present a hybrid VNS metaheuristic to tackle a real Maritime Inventory Routing Problem (MIRP) in a company that explores oil and gas in the Brazilian offshore basin. In the methodology proposed, a linear mathematical model is embedded in the local search procedure to minimize inventory costs. The approach, validated within realistic data, provides low and not regular inventory violations. When compared with a previously developed method, it presents an improved performance, with reduced costs and computational time.

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“…62 -72 © 2021 2011). Recent studies have incorporated inventory decisions into routing, a process called maritime inventory routing, in which an actor has the responsibility for inventory management at one or both ends of the maritime transportation legs and for the ships' routing and scheduling (Sherali and Al-Yakoob 2006a, Sherali and Al-Yakoob 2006b, Christiansen et al 2007, Christiansen and Fagerholt 2010, Song and Furman 2013, Zhang et al 2018, Papageorgiou 2018. Recently, speed optimization for shipping routes has attracted attention because sailing speed determines fuel consumption, which affects a profit maximization approach (Gatica and Miranda 2011, Wen et al 2017, Lakhal 2018.…”

Section: Literature Reviewmentioning

confidence: 99%