Optimization of Heat Integration in Dynamic Multi-agent Differential Evolution Algorithm

For optimization problem of heat integration system, serious nonlinear and non-convex heat exchanger network belonging to multi-extremum and multi-dimensional problems are considered. Dynamic multi-agent differential evolution algorithm is provided to solve the problem. It makes use of sensing capability of multi-agent with dynamic update strategy, which improves formation mechanism of population and mutation mechanism of differential evolution algorithm and globle searching ability in large scale nonlinear system. The algorithm was applied to 10SP2 and 9SP1 cases of heat exchanger network problems. Better total annual cost is obtained, which indicates better globle searching ability of the algorithm.