Paper Info
Title
Solving Multiobjective Optimal Control Problems Using An Improved Scalarization Method
Abstract
Detecting the Pareto optimal points on the Pareto frontier is one of the most important topics in multiobjective optimal control problems (MOCPs). This paper presents a scalarization technique to construct an approximate Pareto frontier of MOCPs, using an improved normal boundary intersection (NBI) scalarization strategy. For this purpose, MOCP is first discretized and then using a grid of weights, a sequence of single objective optimal control problems is solved to achieve a uniform distribution of Pareto optimal solutions on the Pareto frontier. The aim is to achieve a more even distribution of Pareto optimal solutions on the Pareto frontier and improve the efficiency of the algorithm. It is shown that in contrast to the NBI method, where Pareto optimality of solutions is not guaranteed, the obtained optimal solution of the scalarized problem is a Pareto optimal solution of the MOCP. Finally, the ability of the proposed method is evaluated and compared with other approaches using several practical MOCPs. The numerical results indicate that the proposed method is more efficient and provides more uniform distribution of solutions on the Pareto frontier than the other methods, such a weighted sum, normalized normal constraint and NBI.
Year
DOI
Venue
2020
10.1093/imamci/dnaa023
IMA JOURNAL OF MATHEMATICAL CONTROL AND INFORMATION
Keywords
DocType
Volume
multiobjective optimal control problem, scalarization technique, Pareto frontier, normal boundary intersection
Journal
37
Issue
ISSN
Citations 
4
0265-0754
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Gholam Hosein Askarirobati100.34
Akbar Hashemi Borzabadi2209.78
Aghileh Heydari3203.58