Sun D.-Y.Chen C.-L.2019-05-212019-05-21200400219592https://scholars.lib.ntu.edu.tw/handle/123456789/409690In this paper, we propose an algorithm based on basic simulated annealing (SA) to optimize unsteady chemical systems. By parametrizing the control inputs, the system described by a set of differential-algebraic equations is first transferred into a nonlinear programming (NLP) problem. By using a linear function, we furthermore convert discretized control inputs and time grids into the control profile with a variable time length to improve numerical quality. Thus, the discretized control inputs and the corresponding execution time lengths will be considered as a set of decision variables. Then, these decision variables are globally determined by our algorithm with the help of a special integrator to optimize the performance index. In order to exhibit the facility of the proposed algorithm, several typical examples are provided. ? 2004 The Society of Chemical Engineers, Japan.Control parameterizationDynamic optimizationDynamic programmingNonlinear programmingSimulated annealingjournal article10.1252/jcej.37.7112-s2.0-4143051239https://www.scopus.com/inward/record.uri?eid=2-s2.0-4143051239&doi=10.1252%2fjcej.37.711&partnerID=40&md5=42384d3b98817ca99e00bcd1d5c426d3