Meta-heuristic approaches have been used to achieve good
solutions in the heat exchanger network (HEN) synthesis task.
Several meta-heuristic approaches have been proposed in the
literature. Two of the most important techniques are Simulated
Annealing (SA) and Particle Swarm Optimization (PSO). In
general, SA is able to provide good solutions, but with large
computational efforts. PSO is faster than SA in finding good
solutions, but it is not capable of handling discrete variables
properly. In the present work, a bi-level HEN synthesis
approach is presented. SA is used to a single heat exchanger
addition, along with group optimizations to improve PSO
performance. A parallel processing technique is also presented
in order to improve local searching performance. The method
was tested in 3 literature case studies and results were
compared to literature solutions. The solutions presented have
lower Total Annual Costs (TAC) when compared to other
HEN. The proposed method is able to present near-optimal
solutions by more efficiently exploring the search space and
using simple moves for local searches.
Papers presented to the 12th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Costa de Sol, Spain on 11-13 July 2016.