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Media type:
Report;
Text;
E-Book
Title:
Non-linear Goal Programming Using Multi-Objective Genetic Algorithms
Contributor:
Deb, Kalyanmoy
[Author]
imprint:
Universität Dortmund, 2001-10-16
Language:
English
DOI:
https://doi.org/10.17877/DE290R-14973
Origination:
Footnote:
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Description:
Goal programming is a technique often used in engineering design activities primarily to find a compromised solution which will simultaneously satisfy a number of design goals. In solving goal programming problems, classical methods reduce the multiple goal-attainment problem into a single objective of minimizing a weighted sum of deviations from goals. Moreover, in tackling non-linear goal programming problems, classical methods use successive linearization techniques, which are sensitive to the chosen starting solution. In this paper, we pose the goal programming problem as a multi-objective optimization problem of minimizing deviations from individual goals. This procedure eliminates the need of having extra constraints needed with classical formulations and also eliminates the need of any user-defined weight factor for each goal. The proposed technique can also solve goal programming problems having nonconvex trade-off region, which are difficult to solve using classical methods. The efficacy of the proposed method is demonstrated by solving a number of non-linear test problems and by solving an engineering design problem. The results suggest that the proposed approach is an unique, effective, and most practical tool for solving goal programming problems.