Staff and Resource Scheduling at Airports p. 3 GOR Dissertationspreis 2006 Produktionsplanung bei Variantenfliebfertigung p. 11 Scheduling Buses and School Starting Times p. 17 Dynamisches Bestandsmanagement in der Kreislauflogistik p. 23 Periodic Timetable Optimization in Public Transport p. 29 Determining SMB Superstructures by Mixed-Integer Optimal Control p. 37 GOR Diplomarbeitspreis 2006 C...

It is significant to discover a global optimization in the problems dealing with large dimensional scales to increase the quality of decision-making in the mining operation. It has been broadly confirmed that the long-term production scheduling (LTPS) problem performs a main role in mining projects to develop the performance regarding the obtainability of constraints, while maximizing the whole...

The denoising of Lagrangian trajectories based on regularized B-spline is investigated. aim to find systematic criteria for optimization algorithms used in 4D-PTV order optimize the quality measurements turbulent flows as well high-order turbulence statistics. We introduce and adapt this context two innovative tuning strategies which are commonly Tikhonov regularization inverse problems L-curve...

Joint chance-constrained optimization problems under discrete distributions arise frequently in financial management and business operations. These can be reformulated as mixed-integer programs. The size of integer programs is usually very large even though the original problem medium size. This paper studies an augmented Lagrangian decomposition method for finding high-quality feasible solutio...

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...

This paper presents an augmented Lagrangian methodology with a stochastic population based algorithm for solving nonlinear constrained global optimization problems. The method approximately solves a sequence of simple bound global optimization subproblems using a fish swarm intelligent algorithm. A stochastic convergence analysis of the fish swarm iterative process is included. Numerical result...

Active set methods based on the augmented Lagrangian smoothing of nondiier-entiable optimization problems that arise in image restoration are discussed. One-dimensional image restoration problem and two diierent formulations for two-dimensional image restoration problem are given. Both nonmonotone and monotone active set algorithms are described and nite step convergence of the algorithms is co...

In this paper we propose a general framework to characterize and solve the stochastic optimization problems with multiple objectives underlying many real world learning applications. We first propose a projection based algorithm which attains an O(T−1/3) convergence rate. Then, by leveraging on the theory of Lagrangian in constrained optimization, we devise a novel primal-dual stochastic approx...