ABSTRACT Level of repair analysis (LORA) aims to determine the optimal repair policy for complex systems’ components. A repair policy is an a priori decision about which faulty components to discard or repair, and where these actions should take place. Traditionally, LORA models have assumed the maintenance network as pre-defined and identified the resources required to perform the maintenance at each facility as an output. In this paper, the maintenance network itself is an output rather than an input. Other advantages are the ability to deploy different types of resources at the operational level and to allow precise identification of the faulty component. We propose a mixed integer programming (MIP) formulation for the optimization problem, associated with a flow model. Experiments using a set of hypotheticals, but adequate for the purposes of the study, instances provide strong evidence that the formulation’s capabilities can lead to significant cost savings.

AbstractThis work investigates the congestion and traffic flow in a tool plaza, and proposes a methodology for the classification of highway flows and its service levels based on a combination of the Highway Capacity Manual – HCM and Discrete Events Simulation fundaments. The proposed mesoscopic simulation is used to analyze service levels of different physical and operational arrangements of a particular toll gate. The model considers speed functions, toll gate arrivals and departures, as well as events as possible accidents and track change functions when the vehicles arrive at the gate, and offers data for the HCM indexes, which produces the respective service levels. After the application of the model, the results showed the possibility of an operational gain in terms of time in queue, time of congestion and reduction of conflicts, in case the solution is implemented, assisting in decision making. Finally, conclusions are made based on the results of the simulation model.