Optimization of Vacuum Drying Properties for Chlorococcum infusionum Microalgae Moisture Content Using Hybrid Genetic Programming and Genetic Algorithm

Abstract

Biofuel production serves as a viable alternative to conventional energy production systems which primarily relies on fossil fuels. Because of its increased protein and lipid accumulation properties, algal biomass has been deemed a feasible source for biofuel generation among the many types of biomass materials. Microalgal drying process, a preliminary process prior to biofuel production, is a crucial procedure which consumes a lot of energy. Thus, optimization of this process must be considered. As a response, this study aims to determine the optimal vacuum drying parameters such as the biomass thickness, drying temperature and vacuum pressure in reference to the moisture content of the microalgae, Chlorococcum infusionum, using hybrid evolutionary strategies of genetic programming (GP) and genetic algorithm (GA). GP was configured using the GPTIPSv2 tool to generate a symbolic function which is a fundamental element of GA optimization. GA was utilized to generate candidate solutions which were evaluated for goodness of fit through the developed function. Based on the results, this optimization generated parameter values of 5 mm, 69.4°C, and 178.3 mbar for biomass thickness, temperature, and pressure, respectively, which converges at the function value of121.344. This developed technique served as a non-invasive optimization model to computationally determine the optimal microalgal drying parameter values.