BQOA · Binary Quadratic Optimization and Applications

Lines connect the coordinator with its partners.

Project objective

Several combinatorial and discrete optimization problems can be modelled using a quadratic objective function subject to binary constraints; such models are called binary quadratic problems (BQP). These problems are hard to solve in general thus, relaxations are used to find bounds and near optimal solutions. Quadratic programming problems with binary variables arise in many settings, including engineering, finance, transportation, and location problems. The study of linear programming problems with binary variables has been wide ranging, covering many applications and developing many theoretical facets. On the other hand, finding global solutions or even good quality bounds for quadratic programming problems with binary variables has been regarded as a very challenging area of research due to the hardness and complexity of the problem. For the proposed research, we intend to develop new optimization schemes for constrained binary quadratic programming problems by utilizing semidefinite and linear programming techniques. Based on these schemes, we investigate developing efficient algorithms to find global optimal solutions for three challenging applications of binary quadratic programming. In particular, we consider applications in traffic network planning, location and network planning, and satellite communication network planning problems.

Original text from CORDIS.

Participants

• AVIGNON UNIVERSITE · AVIGNON CEDEX 01CoordinatorFrance

Links

• View on CORDIS