Multi-Objective Thermal Desing Optimization of a Shell and Tube Condenser through Global Best Algorithm
Makaleler > Tam Makale · 2017
Yazarlar: Oğuz Emrah Turgut
Deu Muhendislik Fakultesi Fen ve Muhendislik, Uluslararası, 2017, cilt 19, ss 644-665
DOI: 10.21205/deufmd.2017195659
Özet
This study considers Global Best Algorithm (GBEST) for thermoeconomic design of a shell and tube condenser.Design process sustained by the traditional procedures involves tedious and exhaustive iterative calculations which sometimes becomes time consuming and may not lead to economically optimum configuration.Literature studies have shown that solution strategy offered by stochastic optimization methods such as Global Best Algorithm over thermal design of any kind of heat exchanger is promising solution strategy according to the optimum results found in each study.Firstly, optimization performance of the GBEST is assessed with ten benchmark problems and numerical outcomes are compared with those obtained from different literature optimization methods.A case study taken from literature has been solved by GBEST along with famous optimizers of Particle Swarm Optimization and Differential Evolution in the framework of single and multi objective optimization so as to optimize the problem objectives of total cost of heat exchanger and average overall heat transfer coefficient.GBEST not only finds more favourable results than those obtained from the compared optimization algorithms, but also improves the preliminary design taken from literature study.Pareto curve is constructed for multi objective optimization and best solution on the curve is selected by three renowned decision making methods of LINMAP, TOPSIS, and Shannon's entropy theory.Finally, a sensitivity analysis has been performed in order to observe the variational influences of design parameters over optimization objectives.