A simulated annealing algorithm for prioritized multiobjective optimization - Implementation in an adaptive model predictive control configuration

Aggelogiannaki, E; Sarimveis, H

dc.contributor.author	Aggelogiannaki, E	en
dc.contributor.author	Sarimveis, H	en
dc.date.accessioned	2014-03-01T01:25:50Z
dc.date.available	2014-03-01T01:25:50Z
dc.date.issued	2007	en
dc.identifier.issn	1083-4419	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17761
dc.subject	Adaptation	en
dc.subject	Model predictive control (MPC)	en
dc.subject	Multiobjective optimization simulated annealing (SA)	en
dc.subject	Radial basis function (RBF) neural networks	en
dc.subject.classification	Automation & Control Systems	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.classification	Computer Science, Cybernetics	en
dc.subject.other	Adaptive control systems	en
dc.subject.other	Evolutionary algorithms	en
dc.subject.other	Mathematical models	en
dc.subject.other	Multiobjective optimization	en
dc.subject.other	Radial basis function networks	en
dc.subject.other	Random processes	en
dc.subject.other	Simulated annealing	en
dc.subject.other	Adaptive discrete-time model	en
dc.subject.other	Adaptive model predictive control configuration	en
dc.subject.other	Stochastic algorithm	en
dc.subject.other	Model predictive control	en
dc.subject.other	algorithm	en
dc.subject.other	article	en
dc.subject.other	artificial intelligence	en
dc.subject.other	automated pattern recognition	en
dc.subject.other	computer simulation	en
dc.subject.other	decision support system	en
dc.subject.other	feedback system	en
dc.subject.other	methodology	en
dc.subject.other	theoretical model	en
dc.subject.other	Algorithms	en
dc.subject.other	Artificial Intelligence	en
dc.subject.other	Computer Simulation	en
dc.subject.other	Decision Support Techniques	en
dc.subject.other	Feedback	en
dc.subject.other	Models, Theoretical	en
dc.subject.other	Pattern Recognition, Automated	en
dc.title	A simulated annealing algorithm for prioritized multiobjective optimization - Implementation in an adaptive model predictive control configuration	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/TSMCB.2007.896015	en
heal.identifier.secondary	http://dx.doi.org/10.1109/TSMCB.2007.896015	en
heal.language	English	en
heal.publicationDate	2007	en
heal.abstract	This paper presents a new stochastic algorithm for solving hierarchical multiobjective optimization problems. The algorithm is based on the simulated annealing concept and returns a single solution that corresponds to the lexicographic ordering approach. The algorithm optimizes simultaneously the multiple objectives by assigning a different initial temperature to each one, according to its position in the hierarchy. A major advantage of the proposed method is its low computational cost. This is very critical, particularly, for online applications, where the time that is available for decision making is limited. The method is tested in a number of benchmark problems, which illustrate its ability to find near-optimal solutions even in nonconvex multiobjective optimization problems. The results are comparable with those that are produced by state-of-the-art multiobjective evolutionary algorithms, such as the Nondominated Sorting Genetic Algorithm II. The algorithm is further applied to the solution of a large-scale problem that is formulated online, when a multiobjective adaptive model predictive control (MPC) configuration is adopted. This particular control scheme involves an adaptive discrete-time model of the system, which is developed using the radial-basis-function neural-network architecture. A key issue in the success of the adaptation strategy is the introduction of a persistent excitation constraint, which is transformed to a top-priority objective. The overall methodology is applied to the control problem of a pH reactor and proves to be superior to conventional MPC configurations. © 2007 IEEE.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics	en
dc.identifier.doi	10.1109/TSMCB.2007.896015	en
dc.identifier.isi	ISI:000247833000012	en
dc.identifier.volume	37	en
dc.identifier.issue	4	en
dc.identifier.spage	902	en
dc.identifier.epage	915	en