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 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.