SAROTEA · Semidefinite and robust optimization and their economic applications
FP6 — Marie Curie Actions (Human Resources and Mobility)
- Duration
- 2005-03-15 → 2006-04-14
- EU contribution
- €151,521
- Participants
- 1
- Scheme
- IIF
Lines connect the coordinator with its partners. CORDIS does not always give exact coordinates for projects before 2014. These points are placed at city or country level.
Results in brief
Final Activity Report Summary - SAROTEA (Semidefinite and robust optimization and their economic applications)
The project conducted literature survey on some key issues in quantitative call centre management such as building realistic models, developing efficient tools to simulate these models, finding quick approximation formulas for the performance measures of interest, and developing algorithms and software to optimise the staffing and scheduling of agents. As a result, fluid models for multi-server queues (in the context of multi-skill centres) in which different types of calls are handled by different agent groups (with different skill sets) was chosen to be the primary focus. A scientifically notable outcome of this research would be the ability to find optimal call routing strategies by fluid models while guaranteeing appropriate quality of service. Unfortunately, the project had to be terminated before producing any publishable results.
Data: CORDIS, © European Union
Project objective
Robustness to modeling and estimation errors is an issue of critical importance for financial optimization problems because of the serious consequences of making wrong bets. Surprisingly, however, robust optimization has not been widely explored in financi al engineering. The research proposed here formulates robust dynamical models for financial problems and develops semidefmite programming (SDP) based methods for solving them. These models systematically account for parameter uncertainty and robustly updat e error-bounds as more information becomes available over time. In addition, this research extends the semidefmite relaxation methodology to probabilistically robust optimization problems that naturally emerge in the financial context. The other research f ocus of this proposal is on developing semidefmite models for graph theoretic problems such as the traveling salesman problem and network design. These models employ linear matrix inequalities (LMI) to represent 'geometric' constraints, such as graph conne ctivity, specified number of edge/vertex disjoint paths, etc. The optimization problems resulting from these LMI models are, typically, mixed integer semidefmite programs,Currently, mixed semidefmite programs are approximately solved by relaxing the integr ality constraints. However, as computational power increases and the interior point methods for solving semidefmite programs become more efficient, there grows a trend for developing systematic methods of tightening the relaxations - as in the case of line ar programming relaxations of mixed integer programs. As a first step in this direction, I propose to develop several cutting plane strategies for mixed semidefmite programs. Although the problems of interest belong to various application areas, they are l inked in that linear matrix inequalities and semidefmite programming provide the necessary tools to efficiently model and solve them.
Original text from CORDIS.
Participants
- KATHOLIEKE UNIVERSITEIT BRABANT · TILBURGCoordinatorCity levelNetherlands
Links
Data: CORDIS, © European Union