Optimization of Multi-Period Rail Procurement Plan

Rail is one of the most expensive assets in railway infrastructure. Therefore, a well-prepared rail procurement plan could benefit the asset management. For the metro system in Taiwan, the rail procurement plan includes two major uncertainties, namely, currency rates and the global steel price. In this study, we propose deterministic and stochastic optimization models using a scenario-generation process to minimize the expected cost of the rail procurement plan. Results from the case studies demonstrate that the proposed models can successfully incorporate the uncertainties and obtain the optimal procurement plan. The sensitivity analysis on budget, storage capacity, and expiration period also provides the metro operator the best strategy to further lower the procurement cost. Adopting these models in rail procurement planning can improve the process and results of rail asset management.

Synthesis-guided Adversarial Scenario Generation for Gray-box Feedback Control Systems with Sensing Imperfections

In this paper, we study feedback dynamical systems with memoryless controllers under imperfect information. We develop an algorithm that searches for “adversarial scenarios”, which can be thought of as the strategy for the adversary representing the noise and disturbances, that lead to safety violations. The main challenge is to analyze the closed-loop system's vulnerabilities with a potentially complex or even unknown controller in the loop. As opposed to commonly adopted approaches that treat the system under test as a black-box, we propose a synthesis-guided approach, which leverages the knowledge of a plant model at hand. This hence leads to a way to deal with gray-box systems (i.e., with known plant and unknown controller). Our approach reveals the role of the imperfect information in the violation. Examples show that our approach can find non-trivial scenarios that are difficult to expose by random simulations. This approach is further extended to incorporate model mismatch and to falsify vision-in-the-loop systems against finite-time reach-avoid specifications.

Development of a Scenario-based Approach to Simulation Games Management

The Doctoral Thesis is elaborated in the field of scenario-based simulation game management. The essence of simulation games and their role in the learning process is studied, their advantages and disadvantages are identified. The concept of simulation game scenarios is developed that enables efficient game management by using formal methods. An integrated approach to simulation game scenario management is developed and the procedure for scenario generation, simulation and control; as well as its implementation mechanisms, are described.

Energy planning tools applied into urban photovoltaic: the importance of compatibilizing with the constructions

The necessity for an efficient way to develop energy planning in urban environments is increasingly part of the reality of cities. In this sense, tools with the ability to evaluate the installation of distributed generation systems become widely necessary for the elaboration of efficient projects. In this sense, our article aims to evaluate 20 tools from the point of view of urban photovoltaic (PV) planning, considering functionalities such as simulation, scenario generation, bottom-up, availability and application in urban PV; PV is the most widespread power plant in urban environments, with great dissemination capacity.