A Short Excursion to Scalar Optimization: Computing the Set of Approximate Solutions for SOPs

The concepts we have seen in the previous chapter can also be applied to scalar objective optimization problems (SOPs). Unlike for MOPs, where one expects an entire manifold of solutions, the solution of a SOP is typically given by a singleton. That is, if one is “only” interested in the best solution for a given SOP, one can simply keep and update the best found solution during the run of the algorithm. For instance, within an evolutionary algorithm, the best found solution in each step will always be kept in the current population, and there is no need for an additional archiver.