Constraint programming for LNG ship scheduling and inventory management

Goel, Vinod; Slusky, Marla R.; Hoeve, Willem‐Jan van; Furman, Kevin C.; Shao, Yufen

doi:10.1016/j.ejor.2014.09.048

Cited by 59 publications

(35 citation statements)

References 4 publications

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“…In their research, Halvorsen-Weare et al 2013have used simulation to change uncertain environments into certain ones. Goel et al (2015) have made use of the CPLEX software to solve this problem. In this research, MATLAB software with one metaheuristic method, called BPSO, has been used for solving this problem.…”

Section: Discussionmentioning

confidence: 99%

“…For example, Grønhaug et al (2010) have used branch and price method, Goel et al (2012) have applied mixed integer programming (MIP) and arc-flow methods, and Goel et al (2015) have depicted constraint programming to solve LNG issues with inventory routing problem. have proposed a new model to solve LNG routing and scheduling problems considering inventory and berth constraints and Halvorsen-Weare, Fagerholt, & Rönnqvist, (2013) have analyzed the LNG ship routing and scheduling model in an uncertain environment using a mixed integer linear programming (MILP) solved by simulation-based optimization methods.…”

Section: The Significance Of the Studymentioning

confidence: 99%

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A binary particle swarm optimization algorithm for ship routing and scheduling of liquefied natural gas transportation

Yazdi

Kaviani

Emrouznejad

et al. 2019

Transportation Letters

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With the increasing global demands for energy, fuel supply management is a challenging task of today's industries in order to decrease the cost of energy and diminish its adverse environmental impacts. To have a more environmentally friendly fuel supply network, Liquefied Natural Gas (LNG) is suggested as one of the best choices for manufacturers. As the consumption rate of LNG is increasing dramatically in the world, many companies try to carry this product all around the world by themselves or outsource it to third-party companies. However, the challenge is that the transportation of LNG requires specific vessels and there are many clauses in related LNG transportation contracts which may reduce the revenue of these companies, it seems essential to find the best option for them. The aim of this paper is to propose a meta-heuristic Binary Particle Swarm Optimization (BPSO) algorithm to come with an optimized solution for ship routing and scheduling of LNG transportation. The application demonstrates what sellers need to do to reduce their costs and increase their profits by considering or removing some obligations.

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Section: Discussionmentioning

confidence: 99%

Section: The Significance Of the Studymentioning

confidence: 99%

A binary particle swarm optimization algorithm for ship routing and scheduling of liquefied natural gas transportation

Yazdi

Kaviani

Emrouznejad

et al. 2019

Transportation Letters

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show abstract

“…They presented two constraint programming models that rely on a disjunctive scheduling representation of the problem. Also they proposed an iterative search heuristic to generate good feasible solutions for these models [10].…”

Section: Fig3 Gas Procurement Vrp Variantsmentioning

confidence: 99%

Gas-filling stations procurement problem with time windows using a heterogeneous fleet of full tankers

Annouch

Bellabdaoui

2015

2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA)

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In this paper, we address the problem of procurement related to the supply of liquefied petroleum gas (LPG). We are interested in the issue of shipping large quantities of bulk gas (butane and propane) from storage terminals to filling stations storage capacities using a fleet of tankers. The procurement goal is the assignment of quantities of gas to be transferred for each filling station; then, the shipping of these quantities with a heterogeneous fleet of tankers which respects the time schedule of those stations. After a review of literature for the classes of vehicle routing problem with backhauls in oil and gas procurement problems, we will present an integer linear programming formulation (ILP), then, we attempt to solve the problem using a solver, following this by testing and discussing results.

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“…Over-and under-deliveries are accepted, but incur a penalty. In contrast, there are also LNG-IRPs that arise for vertically integrated companies who have control of both the production and consumption side of the supply chain [18,19,11,16,17,31]. In some applications, the opportunity to sell LNG in the spot market using short-term contracts is also present.…”

Section: Maritime Applicationsmentioning

confidence: 99%

Approximate Dynamic Programming for a Class of Long-Horizon Maritime Inventory Routing Problems

Papageorgiou

Cheon

Nemhauser

et al. 2015

Transportation Science

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We study a deterministic maritime inventory routing problem with a long planning horizon. For instances with many ports and many vessels, mixed-integer linear programming (MIP) solvers often require hours to produce good solutions even when the planning horizon is 90 or 120 periods. Building on the recent successes of approximate dynamic programming (ADP) for road-based applications within the transportation community, we develop an ADP procedure to generate good solutions to these problems within minutes. Our algorithm operates by solving many small subproblems (one for each time period) and by collecting information about how to produce better solutions. Our main contribution to the ADP community is an algorithm that solves MIP subproblems and uses separable piecewise linear continuous, but not necessarily concave or convex, value function approximations and requires no off-line training. Our algorithm is one of the first of its kind for maritime transportation problems and represents a significant departure from the traditional methods used. In particular, whereas virtually all existing methods are "MIP-centric," i.e., they rely heavily on a solver to tackle a nontrivial MIP to generate a good or improving solution in a couple of minutes, our framework puts the effort on finding suitable value function approximations and places much less responsibility on the solver. Computational results illustrate that with a relatively simple framework, our ADP approach is able to generate good solutions to instances with many ports and vessels much faster than a commercial solver emphasizing feasibility and a popular local search procedure.

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Constraint programming for LNG ship scheduling and inventory management

Cited by 59 publications

References 4 publications

A binary particle swarm optimization algorithm for ship routing and scheduling of liquefied natural gas transportation

A binary particle swarm optimization algorithm for ship routing and scheduling of liquefied natural gas transportation

Gas-filling stations procurement problem with time windows using a heterogeneous fleet of full tankers

Approximate Dynamic Programming for a Class of Long-Horizon Maritime Inventory Routing Problems

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