In recent papers it has been suggested that human locomotion may be modeled as an inverse optimal control problem. In this paradigm, the trajectories are assumed to be solutions of...
This paper considers online stochastic optimization problems where time constraints severely limit the number of offline optimizations which can be performed at decision time and/...
Stochastic local search (SLS) algorithms have recently been proven to be among the best approaches to solving computationally hard problems. SLS algorithms typically have a number...
In this paper, we study an adaptive random search method based on continuous action-set learning automaton for solving stochastic optimization problems in which only the noisecorr...
We analyze the problem of optimal location of a set of facilities in the presence of stochastic demand and congestion. Customers travel to the closest facility to obtain service; ...