Genetic algorithms in constrained optimization
نویسندگان
چکیده
منابع مشابه
Constrained genetic algorithms and their applications in nonlinear constrained optimization
This paper presents a problem-independent framework that uni es various mechanisms for solving discrete constrained nonlinear programming (NLP) problems whose functions are not necessarily di erentiable and continuous. The framework is based on the rst-order necessary and su cient conditions in the theory of discrete constrained optimization using Lagrange multipliers. It implements the search ...
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The efficiency of a Genetic Algorithm for constrained parameter optimization depends heavily on the ratio of feasible to infeasible area in its rectangular search space. We show an algorithm based on existing mathematical programming methods which improves this ratio assuming a set of linear constraints. We approximate the feasible area by a multidimensional ellipsoid and rotate the original se...
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In this paper we propose two novel approaches for solving constrained multi-objective optimization problems using steady state GAs. These methods are intended for solving real-world application problems that have many constraints and very small feasible regions. One method called Objective Exchange Genetic Algorithm for Design Optimization (OEGADO) runs several GAs concurrently with each GA opt...
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ژورنال
عنوان ژورنال: Mathematical and Computer Modelling
سال: 1996
ISSN: 0895-7177
DOI: 10.1016/0895-7177(96)00014-3