We consider general aggregation/disaggregation techniques to address optimization problems that are expressed with the help of sequential decision processes. Our main goals are threefold: a generic formalism that encompasses the aforementioned techniques ; more efficient algorithms to control the aggregation procedures ; open-source codes that leverage and integrate these algorithms to efficiently solve hard combinatorial problems in different application fields.
We will jointly study two types of approaches, MIP and SAT, to reach our goals.
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This project aims at proposing theoretical and practical results for hard combinatorial optimization problems in an uncertain environment. These problems have in common the fact that the parameters needed to assess the validity of the solution and compute its cost are unknown. Uncertainty in decision making can be caused by several external factors. The most common are related to stochastic parameters (service demand, time needed for a task, prices, …). Incomplete information can also come from the presence of competitors whose policies are not known to the decision maker.
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Robust optimization has evolved as a key paradigm for handling data uncertainty within mathematical optimization problems: it requires little historical information, can be used without characterizing probability distributions and often leads to tractable optimization problems that can be treated with existing deterministic optimization paradigms. However, the picture is more complex when some of the decisions (referred to as recourse decisions) can be adjusted after the uncertain data is known, to mitigate the effects of uncertainty, leading to adjustable robust optimization problems.
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The project:
Strategic Power Systems Development for the Future (PowerDev) funded under an ANR-PEPR studies optimization methods and reliability/resilience engineering applied to large-scale electrical power systems. The project is led by CentraleSupélec at the University of Paris Saclay and is composed of a consortium of higher education institutions across France (CentraleSupelec, UVSQ, University Grenoble Alpes) as well as research organizations (Inria, CNRS).
Research topic and objectives:
Modern power systems are expected to become increasingly complex to design and operate due to the growing number of renewable energy sources (RES).
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Completed projects
One way to improve delivery efficiency is to allow the supplier to manage customer inventory itself. This makes it possible to deliver at the most relevant times, while ensuring a minimum level of stock. In this case, the supplier makes replenishment decisions for products based on specific inventory and supply chain policies. This practice is often described as a win-win model: suppliers save on distribution and production costs because they can coordinate shipments for their different customers, and buyers benefit from a better service cost, and can outsource its inventory management, which is not necessarily its core business.
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