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)

Relaxation timescales and decay of correlations in a long-range interacting quantum simulator

We study the time evolution of correlation functions in long-range interacting quantum Ising models. For a large class of initial conditions, exact analytic results are obtained in arbitrary lattice dimension, both for ferromagnetic and antiferromagnetic coupling, and hence also in the presence of geometric frustration. In contrast to the nearest-neighbour case, we find that correlations decay like stretched or compressed exponentials in time. Provided the long-range character of the interactions is sufficiently strong, pronounced prethermalization plateaus are observed and relaxation timescales are widely separated. Specializing to a triangular lattice in two spatial dimensions, we propose to utilize these results for benchmarking of a recently developed ion-trap based quantum simulator.Comment: 19 pages, 6 figures; v2: one section removed, appendices added; v3: upper bound corrected + minor corrections; v4: as publishe

Measurement of the radiation field surrounding the Collider Detector at Fermilab

We present here the first direct and detailed measurements of the spatial distribution of the ionizing radiation surrounding a hadron collider experiment. Using data from two different exposures we measure the effect of additional shielding on the radiation field around the Collider Detector at Fermilab (CDF). Employing a simple model we parameterize the ionizing radiation field surrounding the detector.Comment: PDF document, 5 pages, including 10 encapsulated postscript figures: Proceedings for the IEEE/NSS-MIC 2003 Conference, Portland, Oregon, October 19-25, 200

Modelling of trends in Twitter using retweet graph dynamics

In this paper we model user behaviour in Twitter to capture the emergence of trending topics. For this purpose, we first extensively analyse tweet datasets of several different events. In particular, for these datasets, we construct and investigate the retweet graphs. We find that the retweet graph for a trending topic has a relatively dense largest connected component (LCC). Next, based on the insights obtained from the analyses of the datasets, we design a mathematical model that describes the evolution of a retweet graph by three main parameters. We then quantify, analytically and by simulation, the influence of the model parameters on the basic characteristics of the retweet graph, such as the density of edges and the size and density of the LCC. Finally, we put the model in practice, estimate its parameters and compare the resulting behavior of the model to our datasets.Comment: 16 pages, 5 figures, presented at WAW 201