A major logistical problem in the Oil and Gas industry is scheduling helicopters to transport its employees to offshore drilling platforms. MemComputing delivers a solution that addresses the problem at scale and provides significant cost savings.
The Oil and Gas industry strives to optimize its production, reduce capital and operating costs, and maintain environmentally friendly operations. Optimization tools are widely used across various divisions to achieve these goals, as they allow for better decision making and improved operational efficiencies. However, there is room for significant improvement as the scale of the mathematical equations behind many of these optimization problems are too complicated for classical computing techniques. Therefore, these companies break up the equations and rely on heuristics or simplifying algorithms, which results in an approximate or less than optimal solution. The result leads to unavoidable operational costs that can reach hundreds of millions of dollars annually per issue [1-5]. Oil and Gas companies canpositively affect the bottom line and improve their profit margins if they utilize MemComputing to address these optimization challenges.
In this work, we study the logistical problem of scheduling a fleet of helicopters for offshore deliveries to oil rigs and support vessels. This problem is often intractable due to the number of helicopters, their different capacities, the number of offshore locations, the cargo, personnel, and time expectations of the deliveries. Here we show that MemComputing provides a near-optimal solution in a matter of seconds where best in class solvers produce rough approximations in hours of computation. The resulting savings in time, fuel costs, reduced maintenance, etc., can deliver $10s to $100s of millions in savings annually depending on the helicopter fleet’s size.