The efficient management of nursing personnel is of vital importance in a hospital’s environment comprising a vast share of the hospital’s operational costs. In the nurse scheduling problem (NSP), the target is to allocate shifts to the nurses in order to satisfy the hospital’s demand during the planning horizon by considering different objective functions. This paper presents a multi-objective...

where w = ((ei)i≥0, (fi)i≥0 ) are disturbances which excite the system in a linear and a bilinear form. We assume that the system is augmented with the output function y i = Cx w i , i ≥ 0. Let ε be a tolerance index on the output. The disturbance w is said to be ε-admissible if ‖y i −yi‖ ≤ ε, ∀ i ≥ 0, where (yi)i≥0 is the output signal associated with the case of an uninfected system. The set ...

A new method is proposed for solving optimization problems with equality constraints and bounds on the variables. In the spirit of Sequential Quadratic Programming and Sequential Linearly-Constrained Programming, the new method approximately solves, at each iteration, an equality-constrained optimization problem. The bound constraints are handled in outer iterations by means of an Augmented Lag...

We consider the solution of nonlinear programs in the case where derivatives of the objective function and nonlinear constraints are unavailable. To solve such problems, we propose an adaptation of a method due to Conn, Gould, Sartenaer, and Toint that proceeds by approximately minimizing a succession of linearly constrained augmented Lagrangians. Our modification is to use a 3 derivative-free ...

In this paper, a simulation-based method for the analysis and design of abstracted models for a stochastic hybrid system is proposed. The accuracy of a model is evaluated in terms of its capability to reproduce the system output for all the realizations of the stochastic input except for a set of (small) probability ε (ε-abstraction). This naturally leads to chance-constrained optimization prob...

This paper presents a filter-based artificial fish swarm algorithm for solving nonconvex constrained global optimization problems. Convergence to an ε-global minimizer is guaranteed. At each iteration k, the algorithm requires a (ρ(k),ε(k))-global minimizer of a bound constrained bi-objective subproblem, where as k→ ∞, ρ(k)→ 0 gives the constraint violation tolerance and ε(k)→ ε is the error bo...

Constrained diffusions in convex polyhedral domains with a general oblique reflection field, and with a diffusion coefficient scaled by a small parameter ε > 0, are considered. Using an interior Dirichlet heat kernel lower bound estimate for second order elliptic operators in bounded domains from [13], certain uniform in ε lower bounds on transition densities of such constrained diffusions are ...