(531a) Comprehensive Planning of Annual Delivery Program for LNG Suppliers
AIChE Annual Meeting
Wednesday, November 10, 2021 - 3:30pm to 3:50pm
Currently, most of the literature present on creating ADPs is to satisfy the LTC demands only considering the inventory and berth management at the supplierâs port. Rakke et al. (2011) developed a rolling horizon heuristic (RHH) for creating LNG annual delivery programs. A Mixed Integer Programming (MIP) formulation was proposed1. StÃ¥lhane et al. (2012) developed a construction and improvement heuristic (CIH) to create ADPs2. Their models allowed under supply of LNG and did not consider inventory and berth management at the customerâs terminal. Mutlu et al. (2016) proposed a MIP model which incorporated split delivery for delivering LNG cargos. Commercial optimizers were not providing even a feasible solution to the MIP model in reasonable time. Small instances were tested but even those instances could not be solved to optimality in a 24-hour run time. So, they proposed a Vehicle Routing Heuristic (VRH) which gave cost effective solutions and outperformed commercial optimizers3. Sheikhtajian et. al. (2020) considered the model proposed by Mutlu et. al. (2015) and developed a model considering shipâs speed as a fuzzy parameter. The aim of the study was to compare shipping expenses of split and non-split delivery strategies considering both deterministic and uncertain situations. They also proposed a meta heuristic as a solution method to solve the problem4. To summarize, some of the models in literature allowed under-supply neglecting inventory and berth management at the customer port, some models did not consider production and delivery of multiple grades of LNG, while others were not able to give optimal solution within reasonable time. We seek to address these gaps through our model.
In this paper, we present a Mixed Integer Linear Programming (MILP) model for delivering LNG shipments from the supplier to LTC customers and a regional spot market. The problem has one supplier and multiple customers spread around the world. The supplier produces and delivers multiple grades of LNG. Our objective is to create an ADP which maximizes profit for the supplier while considering ongoing long-term contracts and regional spot market. The supplier generates revenue by selling excess LNG in spot market. The cost incurred by the supplier in delivering LNG is the sum of transportation and penalty costs if it fails to abide by LTCs. The minimum and maximum production rates, storage capacities at the supplier and customer terminals, transportation time from supplier to customer ports and the slot wise demand at the customers terminal are known a priori. Our model allows over-supply to customers in a reasonable limit and penalizes the supplier for delivering more than the demand. In this paper, we also focus on the inventory and the berth management at the customerâs port. The supplier is responsible for scheduling the heterogeneous fleet of ships. Our model explicitly accounts for loading of ships at the supplierâs port, inventory of LNG at the supplierâs and customerâs terminal. The supplier sends excess LNG to the spot market over the planning horizon. Maintenance of ships is also incorporated in our model. The MILP model is demonstrated on various scenarios having different demands. We get an optimal ship schedule from our model which satisfies the inventory and berth constraints at the supplier and customer ports while fulfilling customers demand with reasonable over-supply. The MILP model for LNG delivery has been implemented in and solved using CPLEX. We believe that the results from this paper would help develop critical insights regarding the tactical planning aspects of the LNG supply chain from the perspective of both supplier and customer.
- J. G. Rakke et al., âA rolling horizon heuristic for creating a liquefied natural gas annual delivery program,â Transp. Res. Part C Emerg. Technol., vol. 19, no. 5, pp. 896â911, Aug. 2011, doi: 10.1016/j.trc.2010.09.006.
- M. StÃ¥lhane, J. G. Rakke, C. R. Moe, H. Andersson, M. Christiansen, and K. Fagerholt, âA construction and improvement heuristic for a liquefied natural gas inventory routing problem,â Comput. Ind. Eng., vol. 62, no. 1, pp. 245â255, Feb. 2012, doi: 10.1016/j.cie.2011.09.011.
- F. Mutlu, M. K. Msakni, H. Yildiz, E. SÃ¶nmez, and S. Pokharel, âA comprehensive annual delivery program for upstream liquefied natural gas supply chain,â Eur. J. Oper. Res., vol. 250, no. 1, pp. 120â130, Apr. 2016, doi: 10.1016/j.ejor.2015.10.031.
- Sheikhtajian, Sanaz, Ali Nazemi, and Majid Feshari. "Marine Inventory-Routing Problem for Liquefied Natural Gas under Travel Time Uncertainty." International Journal of Supply and Operations Management7, no. 1 (2020): 93-111.