Simultaneous synthesis of heat exchanger network with stream split based on quantum-behaved particle swarm optimization algorithm

Simultaneous synthesis problem of heat exchanger network is formulated as a mixed-integer nonlinear programming model. Limited by the Characteristic of the nonlinearity, the convexity and the discontinuity of the model, the classical optimization algorithms which is used to solving the model are easy to fall into local minima. Based on the superstructure model with non-isothermal mixing of split stream, a two-level approach combined with quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to find the optimum structure with a minimum annual cost. In the upper level, QPSO is utilized to generate the structure of the network, while in the lower level, split-stream fractions and heat load of exchangers are optimized by QPSO. Benchmark problems are solved and results show that the two level quantum particle swarm algorithm effectively avoids falling into local minima and it is feasible and effective for heat exchanger network problems.