1. A computerized method for performing multi-objective asset optimization and decision-making using predictive modeling, comprising: building, via a process manager application executing on a processor, at least two predictive models for an asset, the asset comprising a physical machine that is communicatively coupled to the processor, the building comprising: categorizing operational historical data of the asset that is retrieved from a storage device, the operation historical data categorized by at least one of: controllable variables; uncontrollable variables; output objectives; and constraints; selecting at least two output objectives or constraints; and identifying at least one controllable or uncontrollable variable suitable for achieving the at least two output objectives or constraints; inputting, via the process manager application, the at least one controllable or uncontrollable variable to each of the at least two predictive models; validating, via the process manager application, each predictive model; if results of the validating indicate a confidence level above a specified threshold, applying, via the process manager application, a live data stream of inputs from the asset to the predictive models; if results of the validating indicate a confidence level at or below a specified threshold, selecting, via the process manager application, at least one alternative controllable or uncontrollable variable for input to the predictive models; performing, via the process manager application, multi-objective optimization using the predictive models, comprising: specifying search constraints, comprising: upper and lower bounds for each input variable; and tolerance levels representing a range of values for achieving optimal output objectives, and constraints; applying a multi-objective optimization algorithm; and generating a Pareto Frontier, the Pareto Frontier including optimal input-output vectors; using results of the multi-objective optimization, selecting, via the process manager application, from the Pareto Frontier, a Pareto optimal input-output vector for deployment to the asset, the selected Pareto optimal input-output vector specifying an optimal operational state for the asset; and re-configuring the asset, via the process manager application, using the Pareto optimal input-output vector to realize the optimal operational state.
1. A computerized method for performing multi-objective asset optimization and decision-making using predictive modeling, comprising: building, via a process manager application executing on a processor, at least two predictive models for an asset, the asset comprising a physical machine that is communicatively coupled to the processor, the building comprising: categorizing operational historical data of the asset that is retrieved from a storage device, the operation historical data categorized by at least one of: controllable variables; uncontrollable variables; output objectives; and constraints; selecting at least two output objectives or constraints; and identifying at least one controllable or uncontrollable variable suitable for achieving the at least two output objectives or constraints; inputting, via the process manager application, the at least one controllable or uncontrollable variable to each of the at least two predictive models; validating, via the process manager application, each predictive model; if results of the validating indicate a confidence level above a specified threshold, applying, via the process manager application, a live data stream of inputs from the asset to the predictive models; if results of the validating indicate a confidence level at or below a specified threshold, selecting, via the process manager application, at least one alternative controllable or uncontrollable variable for input to the predictive models; performing, via the process manager application, multi-objective optimization using the predictive models, comprising: specifying search constraints, comprising: upper and lower bounds for each input variable; and tolerance levels representing a range of values for achieving optimal output objectives, and constraints; applying a multi-objective optimization algorithm; and generating a Pareto Frontier, the Pareto Frontier including optimal input-output vectors; using results of the multi-objective optimization, selecting, via the process manager application, from the Pareto Frontier, a Pareto optimal input-output vector for deployment to the asset, the selected Pareto optimal input-output vector specifying an optimal operational state for the asset; and re-configuring the asset, via the process manager application, using the Pareto optimal input-output vector to realize the optimal operational state. 8. The computerized method of claim 1 , further comprising selecting, via the process manager application, one of the Pareto optimal input-output vectors for deployment that minimally perturbs the asset from its existing controllable variables configuration.