When supporting decision models must be created, stochastic systems can occasionally be overrun by inconsistent performance specifications and incompatible performance needs, which can be challenging to identify. As a result, offering a variety of solutions that allow for various problem-solving strategies is typically beneficial. These options must satisfy the system's performance specifications while maintaining the greatest degree of differentiation in respective decision spaces. This paper proposes a stochastic bicriteria method for producing sets of options that are as diverse as possible. This stochastic algorithmic approach is computationally effective and simultaneously generates the pre-specified number of maximum unique solution choices in a single computer run of the procedure. On the basis of a case study involving "real world" water resources, the effectiveness of this stochastic MGA technique is shown.
Julian Scott Yeomans
OMIS Area, Schulich School of Business, York University, Toronto, M3J 1P3, Canada
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