Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.774275
Title: Dynamic multi-objective optimization : a two archive strategy
Author: Chen, Renzhi
ISNI:       0000 0004 7961 4813
Awarding Body: University of Birmingham
Current Institution: University of Birmingham
Date of Award: 2018
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Abstract:
Existing studies on dynamic multi-objective optimization mainly focus on dynamic problems with time-dependent objective functions. Few works have put efforts on dynamic problems with a changing number of objectives, or dynamic problems with time-dependent constraints. When problems have time-dependent objective functions, the shape or position of the Pareto-optimal front/set may change over time. However, when dealing with problems with a changing objective number or time-dependent constraints, the challenges are different. Changing number of objectives leads to the expansion or contraction of the dimensions of the Pareto-optimal front/set manifold, while time-dependent constraints may change the shape of feasible regions over time. The existing dynamic handling techniques can hardly handle the changing number of objectives. The state-of-arts in constraints handling techniques are incapable of tackling problems with time-dependent constraints. In this thesis, we present our attempts toward tackling 1) the dynamic multiobjective optimizing problems with a changing number of objectives and 2) multi-objective optimizing problems with time-dependent constraints. Two-archive Evolutionary Algorithms are proposed. Comprehensive experiments are conducted on various benchmark problems for both types of dynamics. Empirical results fully demonstrate the effectiveness of our proposed algorithms.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.774275  DOI: Not available
Keywords: TK Electrical engineering. Electronics Nuclear engineering
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