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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Bibliographic Details
Published in:Soft computing (Berlin, Germany) Vol. 24; no. 11; pp. 7885 - 7905
Main Authors: Sangaiah, Arun Kumar, Tirkolaee, Erfan Babaee, Goli, Alireza, Dehnavi-Arani, Saeed
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2020
Springer Nature B.V
Subjects:
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
Online Access:Get full text
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Summary: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.
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ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-019-04010-6