Solving large-scale retrofit heat exchanger network synthesis problems with mathematical optimization methods

Even if much effort has been put on research within this area, many of the mathematical models consider only grassroot design, whereas most practical cases today seem to be retrofit situations. In addition, these models are likely to be either rigorous but not solvable for bigger (large-scale, real life examples) or deficient and solvable for large-scale problems. This paper takes an attempt to address these problems simultaneously and to develop a rigorous optimization framework based on both a genetic algorithm and a deterministic MINLP-approach and to present an extended model for large-scale retrofit heat exchanger network design problems.