Abstract

Abstract

This view suggests a set of rules for prioritizing investment in a center that mixes stochastic and robust optimization with a portfolio selection and an apparent MCDA layer. Instead of gathering new information, we synthesize the findings at the splitting point, delay and reliability of the provider to parameterize the level of uncertainty. The framework creates evaluation below the limits of finance, pairing of predicted costs with a CVAR or remorse of optimism, while with weights may not be repaired - replicate time, reliability or price. Methodically we extract distribution and correlations from previous instances, compress them into buildings, solve drift and capacitive models with danger and aggregates the hubs to the portfolio boundary. The index converts the risk surface and re-disruption to priority evaluation, so managers can test co-iz-no black cabinets. Literature warns uneven and time -correlated demand; Ignoring it inflates the expected use and is selected closer to excessive nodes. Our algorithm calculates this by prioritizing the increments of abilities that maintain the ranges of service in modest expenditure, final stable under tension. The contribution is a recipe for a choice that reduces distortion from unmarried forecasts and supports the financing of plans. Future work should associate the recipe with operational facts, but the instructions are now applicable.

References

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