On application of stochastic optimization techniques to designing heat exchanger- and water networks

The work addresses systematic simultaneous approaches to designing two process systems: heat exchanger network (HEN) and water network (WN). In both cases stochastic optimization techniques were applied, adaptive random search for WN and genetic algorithms for HEN. In the case of HEN design the approach is tailored for HEN retrofit and accounts for standard apparatus with discrete values of construction parameters. The aim of the paper is twofold. First, it is shown how a general problem analysis can be used for a choice of proper stochastic optimization approach to the problem. The second objective is to explain how to make use of optimization method properties and problem features to enhance efficiency and robustness of optimization. Water network design problem was solved with adaptive random search procedure applied as general-purpose optimizer for superstructure optimization model formulated in equation form. Genetic algorithms approach was applied for HEN retrofit. This is also simultaneous method based on superstructure optimization. Novel superstructure and structure representations were developed to enhance the optimization. The examples of application proved that both approaches allow reaching best solutions from the literature or even better ones in some cases.