This paper discusses the use of several heuristic techniques for problems of combinatorial optimization. We especially consider the advantages and disadvantages of naturally inspired generic techniques like Simulated Annealing, Evolution Strategies, or Genetic Algorithms. This reflection gives a quite intuitive motivation for hybrid approaches that aim to combine advantageous aspects of the cer...

Designing effective algorithms to solve cross-domain combinatorial optimization problems is an important goal for which manifold search methods have been extensively investigated. However, finding optimal combination of perturbation operations solving hard because the different characteristics each problem and discrepancies in strengths operations. The algorithm that works effectively one domai...

Meta-heuristics are an effective paradigm for solving large-scale combinatorial optimization problems. However, the development of such algorithms is often very time-consuming as they have to be designed for a concrete problem class with little or no opportunity for reuse. In this paper, we present a generic software framework that is able to handle different types of combinatorial optimization...

The 18th EURO Summer/Winter Institute (ESWI XVIII) took place during the spring 2000 in Switzerland. The topic of ESWI XVIII, ‘‘Meta-heuristics in Combinatorial Optimization’’, was selected due to its great current scientific interest: indeed, in recent years, several meta-heuristics have proved to be highly efficient for the solution of difficult combinatorial optimization problems. The Instit...

Randomized search heuristics have widely been applied to complex engineering problems as well as to problems from combinatorial optimization. We investigate the runtime behavior of randomized search heuristics and present runtime bounds for these heuristics on some well-known combinatorial optimization problems. Such analyses can help to understand better the working principle of these algorith...