monikriteerioptimointiin

Monikriteerioptimointiin refers to a class of optimization problems where the goal is to simultaneously optimize multiple, often conflicting, objective functions. Unlike single-objective optimization, where a single best solution is sought, multi-criteria optimization aims to find a set of solutions that represent trade-offs between the different objectives. These trade-off solutions are known as Pareto optimal solutions. A solution is Pareto optimal if no other feasible solution exists that can improve one objective without worsening at least one other objective.

The process of finding these Pareto optimal solutions is often referred to as multi-objective optimization or Pareto optimization. The output of a multi-criteria optimization problem is typically a Pareto front, which is the set of all Pareto optimal solutions visualized in the objective space. Decision-makers can then analyze this Pareto front to select a solution that best aligns with their preferences and priorities.

Various algorithms exist to tackle multi-criteria optimization problems, including evolutionary algorithms, gradient-based methods, and goal programming. The choice of algorithm often depends on the nature of the objective functions and constraints, such as linearity, convexity, and differentiability. Applications of multi-criteria optimization are widespread and can be found in fields like engineering design, finance, logistics, environmental management, and artificial intelligence, where complex decisions involve balancing multiple competing goals.