A Stochastic Bicriteria Procedure for Creating System Options
Julian Scott Yeomans · Algorithms research · 2019
Stochastic systems are often overwhelmed by incompatible performance requirements and inconsistent performance specifications that can be difficult to identify when supporting decision models must be constructed. Consequently, it is often advantageous to create a set of dissimilar options that afford distinctive approaches to the problem. These alternatives should satisfy the required system performance criteria and yet be maximally different from each other in their decision spaces. This paper describes a stochastic bicriteria procedure that can generate sets of maximally different alternatives. This stochastic algorithmic approach is both computationally efficient and simultaneously produces the prescribed number of maximally different solution alternatives in a single computational run of the procedure.