Thermal-economic optimization of shell and tube heat exchanger using a new multi-objective optimization method

Many studies have been performed by researchers about Shell and Tube Heat Exchanger but the Multi-Objective Big Bang-Big Crunch Algorithm (MOBBA) technique has never been used in such studies. This study presents application of thermal-economic multi-objective optimization of shell and tube heat exchanger using MOBBA. For an optimal design of a shell and tube heat exchanger, it was first modelled thermally using e-NTU method while Bell-Delaware procedure was applied to estimate its shell side heat transfer coefficient and pressure drop. The MOBBA method was applied to obtain the maximum effectiveness (heat recovery) and the minimum total cost as two objective functions. The results of the optimal designs are a set of multiple optimum solutions, called ‘Pareto optimal solutionsʹ. In order to show the accuracy of the algorithm, a comparison is made with the Non-dominated Sorting Genetic Algorithm (NSGA-II) and MOBBA which are developed for the same problem.