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Title: A nonlinear interval number programming method for uncertain optimization problems
Authors: Jiang, C.
Han, X.
Liu, G.R. 
Liu, G.P.
Keywords: Genetic algorithm
Interval number
Nonlinear programming
Uncertain optimization
Issue Date: 1-Jul-2008
Citation: Jiang, C., Han, X., Liu, G.R., Liu, G.P. (2008-07-01). A nonlinear interval number programming method for uncertain optimization problems. European Journal of Operational Research 188 (1) : 1-13. ScholarBank@NUS Repository.
Abstract: In this paper, a method is suggested to solve the nonlinear interval number programming problem with uncertain coefficients both in nonlinear objective function and nonlinear constraints. Based on an order relation of interval number, the uncertain objective function is transformed into two deterministic objective functions, in which the robustness of design is considered. Through a modified possibility degree, the uncertain inequality and equality constraints are changed to deterministic inequality constraints. The two objective functions are converted into a single-objective problem through the linear combination method, and the deterministic inequality constraints are treated with the penalty function method. The intergeneration projection genetic algorithm is employed to solve the finally obtained deterministic and non-constraint optimization problem. Two numerical examples are investigated to demonstrate the effectiveness of the present method. © 2007 Elsevier B.V. All rights reserved.
Source Title: European Journal of Operational Research
ISSN: 03772217
DOI: 10.1016/j.ejor.2007.03.031
Appears in Collections:Staff Publications

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