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We selected the objective functions that should be maximized for solving most real-word multi-objective optimization problems, which are pairs of the following: partitions separability, internal ...
Many practical decision-making problems involve changing data and parameters with time. Solving such problems requires a custom-designed algorithm that can efficiently handle the repeatedly changing ...
Multiobjective programming is a branch of optimization that deals with problems that have more than one objective function to be minimized or maximized. For example, you might want to design a ...
This project explores the use of Genetic Algorithms (GA) and Differential Evolution (DE) for solving constrained single-objective optimization problems. The implementation includes custom ...
The zero gap of the dual problem based on the augmented Lagrangian objective penalty function for constrained optimization problems is proved. Under some conditions, the saddle point of the augmented ...
Learn how to solve multi-objective nonlinear programming problems with fuzzy parameters using a modified method based on normalized trade-off weights. Explore the stability set and algorithm for ...