An improved chaotic ant swarm algorithm, which synthesizes simultaneously heat exchanger network well, is proposed. Organization variables update strategy and novel dynamic neighborhood topology are introduced to enhance global search ability and local search ability of the algorithm. Two strategies of integer variables are proposed to optimize integer variables represented by heat exchangers. Two heat exchanger network problems with different scale are selected to test the algorithm. Obtained solutions are better than solutions published in literature, which indicates robustness and effectiveness of the algorithm.

Generally, differential evolution (DE) algorithm is easily stuck into local optima as well as suffers from low convergence accuracy when employed for optimization of heat exchanger network. To solve these issues, an opposition-based multi-population parallel differential evolution algorithm is proposed. Firstly, opposite population is built by using initial population. Then, new generation of individuals are generated through information exchange, which is produced by mutated operation between opposite population and its original correspondence. The final step is to retain evolution of multi-population in parallel by applying multi-round opposites, so that the population is enable to keep current solution information and search new solutions in a larger space as well. Computing results of improved DE algorithm on 9sp and 15sp suggests that the method improves population diversity, jumps out local optima and at the same time achieves higher speed and accuracy.

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.

A modified variable charge method based on iterative fluctuation charge model is proposed which is suitable for molecular dynamics simulation of a canonical ensemble.It compensates kinetic energy loss in simulation with thermal bath in the canonical ensemble.Molecular dynamics simulations show that this method has no energy leaking.Number of iteration in the modified method is reduced and the computational efficiency is increased.