Description: Single-objective optimization is an approach where the goal is to maximize or minimize a single objective function, distinguishing it from multi-objective optimization, which considers multiple functions simultaneously. This type of optimization is used across various fields, from engineering to economics, and is based on identifying a clear criterion to optimize. The objective function can represent different aspects, such as costs, benefits, efficiency, or performance, and its formulation is crucial for the success of the optimization process. Techniques employed in single-objective optimization include analytical methods, search algorithms, and heuristics, which allow for finding optimal or near-optimal solutions within a defined solution space. This approach is particularly relevant in situations requiring a clear and direct decision, facilitating decision-making in complex environments. The simplicity of having a single objective allows for easier interpretation of results and more straightforward implementation of the solutions found.
