Solver
A solver is an iterative algorithm that searches for the optimal solution to a defined problem. In this abstract base class, the algorithm is conceptualized as having a main iterative loop. The loop is the main loop that ultimately determines the convergence of the algorithm and recommended solution. Some algorithms have "inner" loops". In general, inner loops are used to control localized search for solutions. If an algorithm has additional inner loops, these can be embedded within the main loop via the subclassing process.
Specialized implementations may have specific methods for determining stopping criteria; however, to avoid the execution of a large number of iterations, the iterative process has a specified maximum number of iterations.
Within the context of simulation optimization, the supplied evaluator promises to execute requests for evaluations of the simulation model at particular design points (as determined by the algorithm). In addition, because of the stochastic nature of the evaluation, the solver may request one or more replications for its evaluation requests. The number of replications may dynamically change, and thus the user needs to supply a function to determine the number of replications per evaluation. Within the framework of the hooks for subclasses, the user could specify more complex procedures for determining the number of replications per evaluation.
Parameters
the maximum number of iterations permitted for the main loop. This must be greater than 0.
a fixed number of replications for each evaluation
a name to help with identifying the solver when multiple solvers are used on a problem
Parameters
the maximum number of iterations permitted for the main loop. This must be greater than 0.
the function controlling how many replications are requested for each evaluation
the reference to the evaluator for evaluating responses from the model
a name to help with identifying the solver when multiple solvers are used on a problem