Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present a scalable computing framework for the solution stochastic multiobjective optimization problems. The proposed framework uses a nested conditional value-at-risk (nCVaR) metric to find compromise solutions among conflicting random objectives.  prove that the associated nCVaR minimization problem can be cast as a standard stochastic programming problem with expected value (linking) constraints.  also show that these problems can be implemented in a modular and compact manner using  PLASMO  (a  Julia -based structured modeling framework) and can be solved efficiently using  PIPS-NLP  (a parallel nonlinear solver).  apply the framework to a CHP design study in which  seek to find compromise solutions that trade-off cost, water, and emissions in the face of uncertainty in electricity and water demands.
['Yankai Cao', 'Luis Fabián Fuentes-Cortés', 'Siyu Chen', 'Victor M. Zavala']
I am writing a research paper on a idea Scalable modeling and solution of stochastic multiobjective optimization problems
[{"from": "human", "value": "I am writing a research paper on a idea Scalable modeling and solution of stochastic multiobjective optimization problems"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present a scalable computing framework for the solution stochastic multiobjective optimization problems. The proposed framework uses a nested conditional value-at-risk (nCVaR) metric to find compromise solutions among conflicting random objectives.  prove that the associated nCVaR minimization problem can be cast as a standard stochastic programming problem with expected value (linking) constraints.  also show that these problems can be implemented in a modular and compact manner using  PLASMO  (a  Julia -based structured modeling framework) and can be solved efficiently using  PIPS-NLP  (a parallel nonlinear solver).  apply the framework to a CHP design study in which  seek to find compromise solutions that trade-off cost, water, and emissions in the face of uncertainty in electricity and water demands."}]