Author:

Keywords:

Science & Technology, Technology, Engineering, Chemical, Engineering, Bioreactors, Chemical reactors, Control, Dynamic optimisation, Multiple objectives, Deterministic optimisation routines, DYNAMIC PROCESS OPTIMIZATION, NORMAL CONSTRAINT METHOD, REDUCED SQP STRATEGY, MULTIOBJECTIVE OPTIMIZATION, BATCH PROCESSES, DESIGN, 0904 Chemical Engineering, 0913 Mechanical Engineering, 0914 Resources Engineering and Extractive Metallurgy, Chemical Engineering, 4004 Chemical engineering

Abstract:

In practical optimal control problems multiple and conflicting objectives are often present, giving rise to a set of Pareto optimal solutions. Although combining the different objectives into a convex weighted sum and varying the weights is the most common approach to generate the Pareto front (when deterministic optimisation routines are exploited), it suffers from several intrinsic drawbacks. A uniform variation of the weights does not necessarily lead to an even spread on the Pareto front, and points in non-convex parts of the Pareto front cannot be obtained [Das, I., Dennis, J.E., 1997. A closer look at drawbacks of minimizing weighted sums of objectives for Pareto set generation in multicriteria optimization problems. Structural Optimization 14, 63-69]. Therefore, this paper investigates alternative approaches based on novel methods as normal boundary intersection [Das, I., Dennis, J.E., 1998. Normal-boundary intersection: a new method for generating the Pareto surface in nonlinear multicriteria optimization problems. SIAM Journal on Optimization 8, 631-657] and normalised normal constraint [Messac, A., Ismail-Yahaya, A., Mattson, C.A., 2003. The normalized normal constraint method for generating the Pareto frontier. Structural and Multidisciplinary Optimization 25, 86-98] to mitigate these drawbacks. The resulting multiple objective optimal control procedures are successfully used in (i) the design of a chemical reactor with conflicting conversion and energy costs, and (ii) the control of a bioreactor with a conflict between yield and productivity. © 2008.