  Approximately 75% of energy used in petrochemical and refining industries is
consumed by furnaces. Operating furnaces at optimal conditions results in huge
amounts of savings. In this paper, we model the furnace efficiency optimization
as a multi-objective problem involving multiple interactions among the
controlled variables and propose a cooperative game based formulation for the
factory of future. The controlled variables are Absorbed Duty and Coil Outlet
Temperature. We propose a comprehensive solution to select the best combination
of manipulated variables (fired duty, throughput and coil inlet temperature)
satisfying multiple criteria using a cooperative game theory approach. We
compare this approach with the standard multi-objective optimization using
NSGA-II and RNSGA-II algorithms.
