Oil and gas downstream supply chain optimization is a difficult problem amid pandemic and current global situation cannot be easily solved by classical computers today. Such problems can be referred to as combinatorial optimization problems (NPHard), typically solved by quantum annealer or computers. An efficient supply chain is one such challenge that if addressed correctly especially in critical times today and in the near future can yield tremendous benefits in terms of reduced cost and resources required. Since using an actual quantum computer is limited today by hardware availability for real-world applications, simulated/vector annealing (SA) can be helpful either working independently or in a hybrid fashion, in combination with a quantum computer. In this presentation, we share how a scalable and hardware accelerated SA solution can independently solve this NP-hard problem. We demonstrate using Simulated Annealing on vector engine-based accelerator system, which can solve downstream supply chain optimization considering real-world complex constraints and compare the results with the existing competing quantum, classical or hybrid solutions.
Authors: Deepak Pathania (NEC Corporation India Private Limited) and Shintaro Momose (NEC Corporation)
