A hybrid multi-objective optimization and decision-making framework (NSGA-II–TOPSIS) for bioethanol production from sago pith waste via microwave-enhanced subcritical water hydrolysis

Abstract

This study presents a hybrid multi-objective optimization and decision-making framework to enhance bioethanol production from sago pith waste (SPW) using microwave-enhanced subcritical water hydrolysis (MW–SWH). A Central Composite Design (CCD) investigated the effects of temperature (180–260 °C), reaction time (10–30 min), microwave power (200–600 W), and water-to-biomass ratio (5–20 mL/g) on sugar and ethanol yields. Response Surface Methodology (RSM) developed predictive models (R² > 0.95), while Non-dominated Sorting Genetic Algorithm II (NSGA-II) simultaneously maximized ethanol yield and minimized energy consumption. TOPSIS identified the most balanced conditions from the Pareto-optimal front. Under optimal conditions, MW–SWH achieved ∼80% sugar yield and ∼71% ethanol yield (27.5 g/100 g SPW), outperforming conventional acid and enzymatic hydrolysis in yield and process efficiency. A specific energy demand of ∼4.72 kWh/kg ethanol was recorded, significantly lower than typical benchmarks. FTIR analysis confirmed effective carbohydrate depolymerization, which correlated with enhanced fermentation performance, yielding an ethanol coefficient of approximately 0.48 g/g. This integrated MW–SWH–NSGA-II–TOPSIS strategy demonstrates a scalable, energy-efficient pathway for valorizing low-lignin, high-starch SPW into bioethanol. The approach shows broader applicability for optimizing lignocellulosic biorefineries and supports sustainable biofuel production aligned with circular economy principles.