Não Linear Programação (NLP) is a branch of otimização matemática that deals with maximizing or minimizing a non-linear função objetivo subject to constraints that may also be non-linear. Unlike programação linear, where both the objective function and the constraints are linear, NLP problems are characterized by at least one non-linear component.
NLP is widely applicable in various fields such as engineering, economics, finance, and operations research. Examples of problems that can be formulated as non-linear programming include otimização de portfólio, resource allocation, and structural optimization in engineering.
O general A forma de um problema de programação não linear pode ser expressa da seguinte maneira:
- Maximizar ou minimizar: f(x)
- Subject to: g_i(x) ≤ 0 for i = 1, …, m (inequality constraints)
- h_j(x) = 0 for j = 1, …, p (equality constraints)
Onde:
- f(x) é a função objetivo não linear.
- g_i(x) são as restrições de desigualdade não linear.
- h_j(x) são as restrições de igualdade não linear.
To solve NLP problems, various algorithms are employed, including gradient-based methods (like the Lagrange multipliers), genetic algorithms, and interior-point methods. The complexity of these problems often requires specialized software and numerical techniques to find an solução ótima.
Non-linear programming is crucial in scenarios where relationships between variables are inherently non-linear, allowing for more realistic modeling of sistemas complexos em comparação com a programação linear.