Description: Bilevel optimization is an approach within model optimization that focuses on solving problems involving two objective functions that must be optimized simultaneously. This type of optimization is fundamental in situations where multiple criteria must be considered, which often occurs in complex decision-making. Unlike unidimensional optimization, where one seeks to maximize or minimize a single function, bi-objective optimization requires a balance between two objectives that may be conflicting. For example, in a product design problem, one might want to maximize quality while minimizing cost. The solution to a bi-objective optimization problem is not limited to a single optimal result but is often represented as a set of optimal solutions, known as the Pareto set. This set allows decision-makers to choose among different alternatives, each with its own advantages and disadvantages. Bi-objective optimization is widely used in various disciplines, including engineering, economics, logistics, and environmental sciences, where decisions must balance multiple factors and objectives.
