Christian Blum, PhD
Senior Research Scientist
Artificial Intelligence Research Institute (IIIA)
Spanish National Research Council (CSIC)


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Plenary Keynote Talk at INISTA 2015

In September 2015 I gave a plenary keynote talk at INISTA 2015 which took place in Madrid, Spain.

Titel: Combining Metaheuristics with ILP Solvers in Combinatorial Optimization

Abstract: Metaheuristics are approximate methods for optimization including, among others, ant colony optimization, evolutionary algorithms and tabu search. The combination of metaheuristics with complete techniques, such as integer linear programming (ILP) solvers, is one of the current lines of research in optimization. The main aim behind such approaches is to exploit the complementary character of different optimization strategies in order to obtain robust algorithms that generate high-quality solutions in reasonable computation times. Given a combinatorial optimization problem, general purpose ILP solvers such as CPLEX are often highly efficient for solving small to medium sized problem instances. This is because they are the result of many years of research. Moreover, they represent efficient implementations of cutting edge technologies in ILP solving. However, naturally they reach their limits with growing problem instance size. One of the motivations for the combination of metaheuristics with ILP solvers such as CPLEX is the aim to take profit from the application of the ILP solver even though the given problem instances are too large for applying these solvers directly.
In this keynote talk we will present several examples of our recent work that have resulted from the motivation outlined above. These examples are centered around the questions of (1) how a given problem instance can be split into subproblems and (2) how a given problem instance can be reduced in such a way that the resulting sub-instance is rather small but still contains high-quality solutions to the original problem instance.

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