We study properties of the solutions to a parametrized constrained optimization problem in Hilbert spaces. A special …

strategy that incorporates both environmental and economic goals. Furthermore, optimization using only a single receptor at a … time resulted in significantly higher reduction in emissions compared to optimization that incorporates all the twelve …-receptor optimization) would not penalize the sources of emission compared to locally optimal emission reduction strategy (i.e., single …

We study properties of the solutions to a parametrized constrained optimization problem in Hilbert spaces. A special …

. This optimization method requires that players adopt a particular type of probability measure space. Here, we introduce … optimization methods to locate novel equilibria. These variational methods can reconcile game theoretic prediction and observed … human behaviours, as we illustrate by resolving the chain store paradox. Our generalized optimization analysis has …

transition probabilities. Our approach is based on an optimization model. More specifically we consider two competing objectives …

individual operational units. This study introduces a stochastic, multi-stage, optimization technique for short-term forecasting …

This paper constructs an alternative investment strategy to portfolio optimization model in the framework of the Mean … normally distributed. The traditional Mean–Variance optimization approach has only one objective, which fails to capture the … problem. The proposed optimization model which is an optimal portfolio strategy is produced for investors of various risk …