Gholam H. Askarirobati - Department of Mathematics, Payame Noor University, P.O.Box ۱۹۳۹۵-۳۶۹۷, Tehran, Iran.
Akbar Hashemi Borzabadi - School of Mathematics and Computer Science, Damghan University, Damghan, Iran.
Aghileh Heydari‎‎‎ - Department of Mathematics, Payame Noor University, Mashhad, Iran.

Detecting the Pareto optimal solutions on the Pareto frontier is one of the most important topics in multiobjective optimal control problems. In real-world control systems, there is needed for the decision-maker to apply their own opinion to find the preferred solution from a large list of Pareto optimal solutions. This paper presents a class of axial preferred solutions for multiobjective optimal control problems in contexts in which partial information on preference weights of objectives is available. These solutions combine both the idea of improvement axis and Pareto optimality with respect to preference information. The axial preferred solution, in addition to taking considerations of decision-makers, provides continuous functions for control ling chemical processes. Numerical results are presented for two problems of chemical processes with two different preferential situations.

‎Multi-‎objective ‎O‎ptimal ‎C‎ontrol‎, ‎ ‎I‎mprovment ‎A‎xis‎, ‎ ‎P‎artial ‎I‎nformation‎, ‎ ‎Axial ‎P‎referred ‎Solutions