Robust optimization and mixed-integer linear programming model for LNG supply chain planning problem

A constant development of gas utilization in domestic households, industry, and power plants has slowly transformed gaseous petrol into a noteworthy wellspring of energy. Supply and transportation planning of liquefied natural gas (LNG) need a great attention from the management of the supply chain...

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Vydané v:	Soft computing (Berlin, Germany) Ročník 24; číslo 11; s. 7885 - 7905
Hlavní autori:	Sangaiah, Arun Kumar, Tirkolaee, Erfan Babaee, Goli, Alireza, Dehnavi-Arani, Saeed
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2020 Springer Nature B.V
Predmet:	Algorithms Artificial Intelligence Case studies Computational Intelligence Control Costs Crude oil prices Decision making Discount rates Energy Engineering Focus Heuristic methods Households Integer programming International relations Inventory Linear programming Liquefied natural gas Manufacturers Mathematical Logic and Foundations Mathematical models Mathematical programming Mechatronics Mixed integer Optimization Parameter sensitivity Power plants Profitability Profits Purchasing contracts Robotics Robustness Suppliers Supply & demand Supply chains Transportation planning China Optimal robustness level Robust optimization Cuckoo optimization algorithm (COA) Liquefied gas sales planning LNG supply
ISSN:	1432-7643, 1433-7479
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Abstract	A constant development of gas utilization in domestic households, industry, and power plants has slowly transformed gaseous petrol into a noteworthy wellspring of energy. Supply and transportation planning of liquefied natural gas (LNG) need a great attention from the management of the supply chain to provide a significant development of gas trading. Therefore, this paper addresses a robust mixed-integer linear programming model for LNG sales planning over a given time horizon aiming to minimize the costs of the vendor. Since the parameter of the manufacturer supply has an uncertain nature in the real world, and this parameter is regarded to be interval-based uncertain. To validate the model, various illustrative examples are solved using CPLEX solver of GAMS software under different uncertainty levels. Furthermore, a novel metaheuristic algorithm, namely cuckoo optimization algorithm (COA), is designed to solve the problem efficiently. The obtained comparison results demonstrate that the proposed COA can generate high-quality solutions. Furthermore, the comparison results of the deterministic and robust models are evaluated, and sensitivity analyses are performed on the main parameters to provide the concluding remarks and managerial insights of the research. Finally, a comparison evaluation is done between the total vendor profit and the robustness cost to find the optimal robustness level.
AbstractList	A constant development of gas utilization in domestic households, industry, and power plants has slowly transformed gaseous petrol into a noteworthy wellspring of energy. Supply and transportation planning of liquefied natural gas (LNG) need a great attention from the management of the supply chain to provide a significant development of gas trading. Therefore, this paper addresses a robust mixed-integer linear programming model for LNG sales planning over a given time horizon aiming to minimize the costs of the vendor. Since the parameter of the manufacturer supply has an uncertain nature in the real world, and this parameter is regarded to be interval-based uncertain. To validate the model, various illustrative examples are solved using CPLEX solver of GAMS software under different uncertainty levels. Furthermore, a novel metaheuristic algorithm, namely cuckoo optimization algorithm (COA), is designed to solve the problem efficiently. The obtained comparison results demonstrate that the proposed COA can generate high-quality solutions. Furthermore, the comparison results of the deterministic and robust models are evaluated, and sensitivity analyses are performed on the main parameters to provide the concluding remarks and managerial insights of the research. Finally, a comparison evaluation is done between the total vendor profit and the robustness cost to find the optimal robustness level.
Author	Goli, Alireza Dehnavi-Arani, Saeed Tirkolaee, Erfan Babaee Sangaiah, Arun Kumar
Author_xml	– sequence: 1 givenname: Arun Kumar orcidid: 0000-0002-0229-2460 surname: Sangaiah fullname: Sangaiah, Arun Kumar email: arunkumarsangaiah@gmail.com organization: School of Computing Science and Engineering, Vellore Institute of Technology (VIT) – sequence: 2 givenname: Erfan Babaee surname: Tirkolaee fullname: Tirkolaee, Erfan Babaee organization: Department of Industrial Engineering, Mazandaran University of Science and Technology – sequence: 3 givenname: Alireza surname: Goli fullname: Goli, Alireza organization: Department of Industrial Engineering, Yazd University – sequence: 4 givenname: Saeed surname: Dehnavi-Arani fullname: Dehnavi-Arani, Saeed organization: Department of Industrial Engineering, Yazd University
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Keywords	Optimal robustness level Robust optimization Cuckoo optimization algorithm (COA) Liquefied gas sales planning LNG supply
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SubjectTerms	Algorithms Artificial Intelligence Case studies Computational Intelligence Control Costs Crude oil prices Decision making Discount rates Energy Engineering Focus Heuristic methods Households Integer programming International relations Inventory Linear programming Liquefied natural gas Manufacturers Mathematical Logic and Foundations Mathematical models Mathematical programming Mechatronics Mixed integer Optimization Parameter sensitivity Power plants Profitability Profits Purchasing contracts Robotics Robustness Suppliers Supply & demand Supply chains Transportation planning
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Title	Robust optimization and mixed-integer linear programming model for LNG supply chain planning problem
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