Crow Search based Multi-objective Optimization of Irreversible Air Refrigerators

Abstract

This study proposes the optimum performance of the irreversible air refrigerators through recently developed metaheuristic algorithm called Crow search algorithm by means of finite time thermodynamics. Finite time thermodynamics is based on choosing the optimum pathways for any kind of thermodynamic system in order to reach the maximum efficiency of the thermodynamic cycle. Handful of objectives for assessing the performance of the irreversible air refrigerators such as coefficient of performance (COP), exergetic efficiency (η II ) , ecological coefficient of performance (ECOP), thermoeconomic optimization (F), and thermoecologic optimization functions (ECF) have been successfully applied on the system. Three optimization scenarios have been studied for the multi objective optimization of irreversible air refrigerators. First scenario evaluates the concurrent optimization of objectives including exergetic efficiency (η II ), coefficient of performance (COP), and ecological coefficient of performance (ECOP). In second scenario, coefficient of performance (COP), thermoeconomic parameter (F), and thermoecological coefficient of performance (ECOP) have been simultaneously maximized to retain optimum working point of the cycle. Third case studies the simultaneous optimization of the imposed objectives such as second law efficiency (η II ), coefficient of performance (COP), and thermoecological function (ECF). Widely known decision-making theorems of LINMAP, TOPSIS, and Shannon’s entropy theorem have been applied on the Pareto curve constructed by the non-dominated solutions to decide the most favorable solution on the frontier.