Superstructure optimization of a microalgal biorefinery design with life cycle assessment‐based and economic objectives

Abstract We present a multi‐objective optimization framework for the design of an algal biorefinery with multiple target products. Four environmental endpoint indicators and economic performance are used as objective functions following life cycle assessment (LCA) methodology. The process alternatives modeled superstructure covering total 720 feasible routes. proposed method optimizes not only route but simultaeously discrete continuous parameters within units. A genetic algorithm (MOGA) is to solve this nonlinear mixed‐integer problem extraction procedures all macromolecular fractions. For extractions, liquid–liquid equilibria (LLE) predicted quantum chemical calculations. microalgae marine diatom Phaeodactylum tricornutum considered case study, including cultivation extraction‐supported fractionation wet biomass harvest products eicosapentaenoic acid (EPA), laminarin fucoxanthin. 2‐Butanol proved be preferred solvent initial step biomass. Nutrients production cause most impact overall process. Python package integrating LCA provided open source software. It applicable any system task involving objectives.