Title of article :
Solving Multi-Objective Optimal Control Problems of Chemical Processes Using Hybrid Evolutionary Algorithm
Author/Authors :
ASKARIROBATI, GHOLAM HOSEIN Department of Mathematics - Payame Noor University , Tehran , Iran , HASHEMI−BORZABADI, AKBAR Department of Mathematics and Computer Science - Damghan University, Damghan, Iran , HEYDARI, AGHILEH Department of Mathematics - Payame Noor University, Tehran, Iran
Abstract :
This paper applies an evolutionary optimization
scheme , inspired by Multi-objective Invasive Weed
Optimization (MOIWO) and Non-dominated Sorting
(NS) strategies , to find approximate solutions for multiobjective
optimal control problems (MOCPs) . The
desired control function may be subjected to severe
changes over a period of time . In response to
deficiency , the process of dispersal has been modified
in the MOIWO . This modification will increase the
explorative power of the weeds and reduces the search
space gradually during the iteration process . The
performance of the proposed algorithm is compared
with conventional Non-dominated Sorting Genetic
Algorithm (NSGA-II) and Non-dominated Sorting
Invasive Weed Optimization (NSIWO) algorithm .
Keywords :
Fed Batch Reactor , Invasive weed optimization , Non-dominated sorting , Pareto optimal frontier , Multi-objective optimal control
