Stochastic Optimization Tools for Water-Heat Nexus Problems

This aim of this work is to provide a framework for application of Simulated Annealing (SA) Algorithm for solving Water - Heat Nexus problems for Industrial Cities. The combined water-heat network synthesis problem has been formulated into a Mixed Integer Non-Linear Programming (MINLP) and this work describes the various components of the framework needed to handle it. The SA algorithm converges asymptotically across several runs. Apart from the best solution, this tool stores multiple solutions with varying degree of performance. The application of this algorithm has been illustrated with a case study and the benefits of metaheuristics search techniques have been highlighted.