We develop a novel Mean-Max Drawdown portfolio optimization approach using buy-and-hold portfolios. The optimization is performed utilizing a multi-objective evolutionary algorithm on a sample of S&P 100 constituents. Our optimization procedure provides portfolios with better Mean-Max Drawdown...

We develop a numerical model that simulates the evolution of a virtual population with an incentive and ability-based wage, capital yield from savings, social welfare system, and total income subject to taxation and political turnovers. Meta-heuristics, particle swarm optimization (PSO) in...

Considering a temporal dimension allows for the delivery of rolling solutions to complex real-world problems. Moving forward in time brings uncertainty, and large margins for potential error in solutions. For the multi-year crop planning problem, the largest uncertainty is how the climate will...