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Jeudi 17 Mars
| Heure: |
12:30 - 13:30 |
| Lieu: |
Salle B107, bâtiment B, Université de Villetaneuse |
| Résumé: |
A Tailored Benders Decomposition Approach for Last-mile Delivery with Autonomous Robots |
| Description: |
Ivana Ljubic This work addresses an operational problem of a logistics service provider that consists of finding an optimal route for a vehicle carrying customer parcels from a central depot to selected facilities, from where autonomous devices like robots are launched to perform last-mile deliveries. The objective is to minimize a tardiness indicator based on the customer delivery deadlines. We provide a better understanding of how three major tardiness indicators can be used to improve the quality of service by minimizing the maximum tardiness, the total tardiness, or the number of late deliveries. We study the problem complexity, devise a unifying Mixed Integer Programming formulation and propose an efficient branch-and-Benders-cut scheme to deal with instances of realistic size. Numerical results show that this novel Benders approach with a tailored combinatorial algorithm for generating Benders cuts largely outperforms all other alternatives. In our managerial study, we vary the number of available facilities, the coverage radius of autonomous robots and their speed, to assess their impact on the quality of service and environmental costs. Joint work with: L. Alfandari and M.M. de Silva |
Jeudi 7 Avril
| Heure: |
11:30 - 12:30 |
| Lieu: |
Salle B107, bâtiment B, Université de Villetaneuse |
| Résumé: |
Quantum Computing for Process Systems Engineering |
| Description: |
David Bernal Neira Optimization problems arise in different areas of Process Systems Engineering (PSE), and solving these problems efficiently is essential for addressing important industrial applications.
Quantum computers have the potential to efficiently solve challenging nonlinear and combinatorial problems. However, available quantum computers cannot solve practical problems; they are limited to small sizes and do not handle constraints well. In this talk, we propose hybrid classical-quantum algorithms to solve mixed-integer nonlinear problems (MINLP) and apply decomposition strategies to break down MINLPs into Quadratic Unconstrained Binary Optimization (QUBO) subproblems that can be solved by quantum computers. We will also cover different approaches to solving Quadratic Unconstrained Binary Optimization (QUBO) problems through unconventional computation methods, including but not limited to Quantum algorithms, and discuss how these approaches lead to algorithms able to outperform classical solution approaches |
Jeudi 21 Avril
| Heure: |
10:30 - 11:30 |
| Lieu: |
Salle B107, bâtiment B, Université de Villetaneuse |
| Résumé: |
Fast algorithms for some parametric optimization problems |
| Description: |
Hassan Aissi Parametric optimization is a rich field with applications ranging from sensitivity analysis, Lagrangian relaxation, multiobjective optimization, and minimum-ratio optimization. We consider in this talk some parametric problems related to the minimum cut, in which we are given a graph G=(V,E) with edge costs that are affine functions of a parameter ???d. We develop strongly polynomial algorithms for these problems that are faster than known techniques. |
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