Model based decision support for planning of road maintenance

In this article we describe a Decision Support Model, based on Operational Research methods, for the multi-period planning of maintenance of bituminous pavements. This model is a tool for the road manager to assist in generating an optimal maintenance plan for a road. Optimal means: minimising the Net Present Value of maintenance costs, while the plan is acceptable in terms of technical admissibility, resulting quality, etc. Global restrictions such as budget restrictions can also be imposed.\ud \ud Adequate grouping of maintenance activities in view of quantity discounts is an important aspect of our model. Our approach is to reduce the complexity of the optimisation by hierarchical structuring in four levels. In the lowest two levels maintenance per lane sector is considered, first with an unbounded planning horizon and next with a bounded planning horizon and time-windows for maintenance. The grouping of maintenance activities for a specific road is the topic of the third level. At the fourth level, which we will not consider in this article, the problem of optimal assignment of the available maintenance budgets over a set of roads or road sections takes place. Here, some results are presented to demonstrate the effects of grouping and to show that this hierarchical approach gives rise to improvements compared with previous work

Managing fisheries in a changing climate

No need to wait for more information: industrialized fishing is already wiping out stocks

The optimal legal retirement age in an OLG model with endogenous labour supply

The long run welfare implications of the legal retirement age are studied in a perfect foresight overlapping-generations model where agents live for two periods. Agents’ lifetime is divided between working life and retirement by a legal retirement age controlled by the government whereas agents, besides savings, control the intensive margin or "yearly" labour supply. The legal retirement age is utilized to dampen distortionary effects of payroll taxes and public pension annuities and promote capital accumulation. We show that a social optimal legal retirement age exists and how it depends on whether payroll taxes or benefit annuities ensures budget balance of the PAYG pension system.Optimal legal retirement age; pay-as-you-go-pension systems; overlapping-generations model

Inventory control for a non-stationary demand perishable product: comparing policies and solution methods

This paper summarizes our findings with respect to order policies for an inventory control problem for a perishable product with a maximum fixed shelf life in a periodic review system, where chance constraints play a role. A Stochastic Programming (SP) problem is presented which models a practical production planning problem over a finite horizon. Perishability, non-stationary demand, fixed ordering cost and a service level (chance) constraint make this problem complex. Inventory control handles this type of models with so-called order policies. We compare three different policies: a) production timing is fixed in advance combined with an order up-to level, b) production timing is fixed in advance and the production quantity takes the age distribution into account and c) the decision of the order quantity depends on the age-distribution of the items in stock. Several theoretical properties for the optimal solutions of the policies are presented. In this paper, four different solution approaches from earlier studies are used to derive parameter values for the order policies. For policy a), we use MILP approximations and alternatively the so-called Smoothed Monte Carlo method with sampled demand to optimize values. For policy b), we outline a sample based approach to determine the order quantities. The flexible policy c) is derived by SDP. All policies are compared on feasibility regarding the α-service level, computation time and ease of implementation to support management in the choice for an order policy.National project TIN2015-66680-C2-2-R, in part financed by the European Regional Development Fund (ERDF)

Conjugate gradient acceleration of iteratively re-weighted least squares methods

Iteratively Re-weighted Least Squares (IRLS) is a method for solving minimization problems involving non-quadratic cost functions, perhaps non-convex and non-smooth, which however can be described as the infimum over a family of quadratic functions. This transformation suggests an algorithmic scheme that solves a sequence of quadratic problems to be tackled efficiently by tools of numerical linear algebra. Its general scope and its usually simple implementation, transforming the initial non-convex and non-smooth minimization problem into a more familiar and easily solvable quadratic optimization problem, make it a versatile algorithm. However, despite its simplicity, versatility, and elegant analysis, the complexity of IRLS strongly depends on the way the solution of the successive quadratic optimizations is addressed. For the important special case of $\textit{compressed sensing}$ and sparse recovery problems in signal processing, we investigate theoretically and numerically how accurately one needs to solve the quadratic problems by means of the $\textit{conjugate gradient}$ (CG) method in each iteration in order to guarantee convergence. The use of the CG method may significantly speed-up the numerical solution of the quadratic subproblems, in particular, when fast matrix-vector multiplication (exploiting for instance the FFT) is available for the matrix involved. In addition, we study convergence rates. Our modified IRLS method outperforms state of the art first order methods such as Iterative Hard Thresholding (IHT) or Fast Iterative Soft-Thresholding Algorithm (FISTA) in many situations, especially in large dimensions. Moreover, IRLS is often able to recover sparse vectors from fewer measurements than required for IHT and FISTA.Comment: 40 page

Interplay of Soundcone and Supersonic Propagation in Lattice Models with Power Law Interactions

We study the spreading of correlations and other physical quantities in quantum lattice models with interactions or hopping decaying like $r^{-\alpha}$ with the distance $r$. Our focus is on exponents $\alpha$ between 0 and 6, where the interplay of long- and short-range features gives rise to a complex phenomenology and interesting physical effects, and which is also the relevant range for experimental realizations with cold atoms, ions, or molecules. We present analytical and numerical results, providing a comprehensive picture of spatio-temporal propagation. Lieb-Robinson-type bounds are extended to strongly long-range interactions where $\alpha$ is smaller than the lattice dimension, and we report particularly sharp bounds that are capable of reproducing regimes with soundcone as well as supersonic dynamics. Complementary lower bounds prove that faster-than-soundcone propagation occurs for $\alpha<2$ in any spatial dimension, although cone-like features are shown to also occur in that regime. Our results provide guidance for optimizing experimental efforts to harness long-range interactions in a variety of quantum information and signaling tasks.Comment: 20 pages, 8 figure