Derivative-Free Chemical Process Synthesis by Memetic Algorithms Coupled to Aspen Plus Process Models

Abstract Design optimization problems of chemical processes are characterized by a large number of discrete and continuous design decisions, highly non-linear models and multi-modal continuous subspaces. In our previous work, we introduced a derivative-free memetic algorithm (MA) for design optimization which is a combination of an evolutionary algorithm (EA) and a derivative-free optimization (DFO) method. The EA addresses the global optimization of all design variables, whereas the DFO method locally optimizes the continuous sub-problems that arise by fixing the discrete variables with respect to design specifications. The MA calls the simulation software Aspen Plus to simulate the design alternatives. In this contribution, the MA is extended to consider two objectives. Therefore, the selection procedure of the MA is replaced by a multi-objective selection and the continuous optimization problem which is addressed by the DFO method is reformulated.