This research deals with the advanced exergy and exergoeconomic analyses and multi-objective optimization of an internal auto-cascade refrigeration cycle. Butane is used as the refrigerant and all heat exchangers are modeled by considering pressure drops. Sensitivity study is carried out to assess the variation of exergetic and economic improvement potentials; namely, total avoidable exergy destruction, total avoidable exergy destruction cost and total avoidable investment cost rates to the compressor mass flow rate, condenser, refrigerator evaporator and freezer evaporator inlet temperatures. Parametric study indicates that the condenser inlet temperature growth improves the total avoidable exergy destruction within 88.19%, the total avoidable investment cost rate increases by about 126.92% and 3.68% as compressor inlet mass and refrigerator evaporator inlet temperature rise, respectively and the increment of refrigerator evaporator inlet temperature shows a positive effect on the total avoidable exergy destruction cost rate. In addition, improvement potentials are maximized by applying Non-dominated Sort Genetic Algorithm-II. The multi-objective optimization indicates 76.78%, 38.66% and 103.38% improvements in total avoidable exergy destruction rate, total avoidable investment and total avoidable exergy destruction cost rates, respectively relative to the base design point. (C) 2017 Elsevier Ltd. All rights reserved.