Metaheuristics have shown promising performance in solving various deterministic optimization problems, but their performance may deteriorate drastically when tackling problems containing stochastic multiple objectives that should be optimized simultaneously. In recent years, a large amount of...

Solving optimization problems becomes a central theme not only on operational research but also on several research areas like robotic, medicine, economic etc. The number of support decision problems that can be formalized as an optimization problem is growing rapidly. This study represents a...

In this paper we give an overview of algorithms developed to aid catalyst optimization at the Mexican Institute of Petroleum. We present a methodology that uses an evolutionary approach and ideas from tabu search and simulated annealing to guide the search for optimum catalytic materials based...

Hedge funds offer desirable risk-return profiles; but we also find high management fees, lack of transparency and worse, very limited liquidity (they are often closed to new investors and disinvestment fees can be prohibitive). This creates an incentive to replicate the attractive features of...

Several approaches for subset recovery and improved forecasting accuracy have been proposed and studied. One way is to apply a regularization strategy and solve the model selection task as a continuous optimization problem. One of the most popular approaches in this research field is given by...

Pena's method of construction of a synthetic indicator is very sensitive to the order in which the constituent variables (whose linear aggregation yields the synthetic indicator) are arranged. Due to this, Pena's method can at present give only an arbitrary synthetic indicator whose...

Linear regression is widely-used in finance. While the standard method to obtain parameter estimates, Least Squares, has very appealing theoretical and numerical properties, obtained estimates are often unstable in the presence of extreme observations which are rather common in financial time...