Hybridized optimization approaches to the scheduling of multi-period mixed-Btu natural gas products

Decisions regarding the buying, storing and selling of natural gas are difficult facing the high volatility of prices and uncertain demand. The increasing availability of low-Btu gas complicates decisions faced by investors and operational planners of consumers of natural gas. This study examines multiple approaches to maximizing profits by optimally scheduling the purchase and storage of two gas products of different energy densities and the sales of the same combined with a blended third product. Three approaches, a Branch and Bound-linear programming hybrid, a stochastic search algorithm-linear programming hybrid, and a pure random search are developed and tested in simulated environments. To make each technique computationally tractable, constraints on the units of product moved in each transaction are implemented. Using numerical data, the three approaches are tested, analyzed and compared statistically and graphically along with computer performance information. The result provides a basis for planners to improve decision making.