Description: Multi-objective optimization is an approach in the field of mathematical optimization that focuses on solving problems involving more than one objective function to be optimized simultaneously. Unlike traditional optimization, which seeks to maximize or minimize a single function, multi-objective optimization considers multiple criteria that may conflict with each other. This means that improving one objective may degrade performance in another. This type of optimization is crucial in situations where decisions must balance different factors, such as cost, time, quality, and sustainability. Solutions to these problems are not limited to a single optimal result but are represented as a set of solutions known as the Pareto front, where each solution is optimal in the sense that no objective can be improved without worsening another. Multi-objective optimization is applied in various fields, including engineering, economics, logistics, and system design, where decisions must consider multiple dimensions of performance, efficiency, and trade-offs between competing objectives.
