This paper reports about research projects of the University of Paderborn in the field of distributed combinatorial optimization. We give an introduction into combinatorial optimization and a brief definition of some important applications. As a first exact solution method we describe branch & bound and present the results of our work on its distributed implementation. Results of our distributed implementation of iterative deepening conclude the first part about exact methods. In the second part we give an introduction into simulated annealing as a heuristic method and present results of its parallel implementation. This part is concluded with a brief description of genetic algorithms and some other heuristic methods together with some ...
Genetic algorithms are one example of the use of a random element within an algorithm for combinator...
Abstract. This report summarizes the meeting on Combinatorial Optimization where new and promising d...
The paper presents an analysis of the use of optimization algorithms in parallel solutions and distr...
With combinatorial optimization we try to find good solutions for many computationaly difficult prob...
Combinatorial optimization is a way of finding an optimum solution from a finite set of objects. For...
Simulated annealing has proven to be a good technique for solving hard combinatorial optimization p...
In this paper, the Evolutionary Simulated Annealing (ESA) algorithm, its distributed implementation ...
In the proposed algorithm, several single population genetic algorithms with different cross-over an...
The problem addressed here is to orthogonally pack a given set of box shaped items into the minimum ...
This talk will present a tutorial on the implementation and use of metaheuristics and approximation ...
This paper presents a short (and not exhaustive) introduction to the most used exact, approximation,...
Problems in combinatorial optimization, whether they are solved exactly or approximately by a heuris...
In this paper, we review parallel search techniques for approximating the global optimal solution of...
Problems arising in different areas such as numerical methods, simulation or optimization can be eff...
This work was motivated by the need of exploiting the potential of distributed paralelism in combina...
Genetic algorithms are one example of the use of a random element within an algorithm for combinator...
Abstract. This report summarizes the meeting on Combinatorial Optimization where new and promising d...
The paper presents an analysis of the use of optimization algorithms in parallel solutions and distr...
With combinatorial optimization we try to find good solutions for many computationaly difficult prob...
Combinatorial optimization is a way of finding an optimum solution from a finite set of objects. For...
Simulated annealing has proven to be a good technique for solving hard combinatorial optimization p...
In this paper, the Evolutionary Simulated Annealing (ESA) algorithm, its distributed implementation ...
In the proposed algorithm, several single population genetic algorithms with different cross-over an...
The problem addressed here is to orthogonally pack a given set of box shaped items into the minimum ...
This talk will present a tutorial on the implementation and use of metaheuristics and approximation ...
This paper presents a short (and not exhaustive) introduction to the most used exact, approximation,...
Problems in combinatorial optimization, whether they are solved exactly or approximately by a heuris...
In this paper, we review parallel search techniques for approximating the global optimal solution of...
Problems arising in different areas such as numerical methods, simulation or optimization can be eff...
This work was motivated by the need of exploiting the potential of distributed paralelism in combina...
Genetic algorithms are one example of the use of a random element within an algorithm for combinator...
Abstract. This report summarizes the meeting on Combinatorial Optimization where new and promising d...
The paper presents an analysis of the use of optimization algorithms in parallel solutions and distr...