Robust multi-sensor scheduling for multi-site surveillance

This paper presents mathematical programming techniques for solving a class of multi-sensor scheduling problems. Robust optimization problems are formulated for both deterministic and stochastic cases using linear 0–1 programming techniques. Equivalent formulations are developed in terms of cardinality constraints. We conducted numerical case studies and analyzed the performance of optimization solvers on the considered problem instances. Keywords Mathematical programming · Multi-sensor scheduling · Combinatorial optimization · Robust optimization · Risk measures

• Type: Journal
• Year: 2011
• Where: JCO
• Authors: Nikita Boyko, Timofey Turko, Vladimir Boginski, David E. Jeffcoat, Stanislav Uryasev, Grigoriy Zrazhevsky, Panos M. Pardalos
• Keywords: Cardinality Constraints, JCO 2011, Mathematical Programming Techniques, Robust Optimization