A Novel Evolutionary Algorithm Based on Decomposition and Adaptive Weight Adjustment for Synthesis Gas Production

Synthesis gas production is widely used in chemical industries. Carbon dioxide reforming, steam reforming and partial-oxidation of methane are the main synthesis gas production methods. In this work, three objectives of maximize the selectivity of carbon monoxide, maximize the conversion of methane and minimize the hydrogen to carbon monoxide mole ratio which contain the variables of temperature, gas hourly space velocity and the oxygen to methane mole ratio are optimized to improve the productivity of synthesis gas production, and a novel evolutionary algorithm based on decomposition and adaptive weight adjustment is designed to solve multi-objective optimization problem (MOP). This proposed algorithm is compared with classic MOEA/D, NSGA-II, and simulation results show that the proposed algorithm is better at solving this multi-objective optimization problem than MOEA/D and NSGA-II.