Representative scenario construction and preprocessing for robust combinatorial optimization problems

On Scenario Aggregation to Approximate Robust Combinatorial Optimization Problems

As most robust combinatorial min-max and min-max regret problems with discrete uncertainty sets are NP-hard, research in approximation algorithm and approximability bounds has been a fruitful area of recent work. A simple and well-known approximation algorithm is the midpoint method, where one takes the average over all scenarios, and solves a problem of nominal type. Despite its simplicity, th...

Scenario Reduction and Scenario Tree Construction for Power Management Problems

Portfolio and risk management problems of power utilities may be modeled by multistage stochastic programs. These models use a set of scenarios and corresponding probabilities to model the multivariate random data process (electrical load, stream flows to hydro units, and fuel and electricity prices). For most practical problems the optimization problem that contains all possible scenarios is t...

On Scenario Aggregation to Approximate Robust Optimization Problems

As most robust combinatorial min-max and min-max regret problems with discrete uncertainty sets are NP-hard, research into approximation algorithm and approximability bounds has been a fruitful area of recent work. A simple and wellknown approximation algorithm is the midpoint method, where one takes the average over all scenarios, and solves a problem of nominal type. Despite its simplicity, t...

Efficient preprocessing for VLSI optimization problems

Advances in technology for the manufacturing of integrated circuits have resulted in extremely large, and time consuming, problems on how to lay out components for optimal circuit performance. These problems can be written as mixed integer programs which are easily relaxed to linear programs with a very high number of variables and constraints. The relaxed programs can often be solved by applyi...

Construction heuristics for hard combinatorial optimisation problems