Add to ORKGA new genetic algorithm for the macro cell placement problem is presented. The algorithm is based on a gen-eralization of the two-dimensional bin packing problem. The genetic encoding of a macro cell placement and the corresponding genetic operators are described. The al-gorithm has been tested on ikfCNL ’ benchmarks, and the quality of the produced placements are comparable to the best published results.
This paper considers a new variant of the two-dimensional bin packing problem where each rectangle i...
We present a novel multi-population biased random-key genetic algorithm (BRKGA) for the 2D and 3D bi...
This paper presents an approach to the automatic place-ment of a combination of macro blocks and sta...
Abstract — Genetic algorithms have proven to be a well-suited technique for solving selected combina...
Analog macrocell placement is an NP-hard problem. This paper presents an attempt to solve this probl...
A new approximation algorithm is presented for the efficient handling of large macro-cell placement ...
Cutting and packing problems are combinatorial optimisation problems. In most manufacturing situatio...
The topic of this Ph.D. thesis is the application of evolution-based algorithms (EAs) to various hig...
This paper proposes an optimization approach for macro-cell placement which minimizes the chip area...
Practical analog layout synthesis techniques have been the subject of active research for the past t...
This research investigates the application of the Genetic Algorithm for four VLSI layout problems, G...
<p>For every set of bin packing data there exists a unique ordering which produces the optimal solut...
ISBN :978-0-387-73660-0New technologies present a widely range of challenges in the design of standa...
A two-dimensional bin-packing problem is considered, where bins have processing times, and rectangle...
This paper presents a novel genetic algorithm for analog module placement. It is based on a generali...
This paper considers a new variant of the two-dimensional bin packing problem where each rectangle i...
We present a novel multi-population biased random-key genetic algorithm (BRKGA) for the 2D and 3D bi...
This paper presents an approach to the automatic place-ment of a combination of macro blocks and sta...
Abstract — Genetic algorithms have proven to be a well-suited technique for solving selected combina...
Analog macrocell placement is an NP-hard problem. This paper presents an attempt to solve this probl...
A new approximation algorithm is presented for the efficient handling of large macro-cell placement ...
Cutting and packing problems are combinatorial optimisation problems. In most manufacturing situatio...
The topic of this Ph.D. thesis is the application of evolution-based algorithms (EAs) to various hig...
This paper proposes an optimization approach for macro-cell placement which minimizes the chip area...
Practical analog layout synthesis techniques have been the subject of active research for the past t...
This research investigates the application of the Genetic Algorithm for four VLSI layout problems, G...
<p>For every set of bin packing data there exists a unique ordering which produces the optimal solut...
ISBN :978-0-387-73660-0New technologies present a widely range of challenges in the design of standa...
A two-dimensional bin-packing problem is considered, where bins have processing times, and rectangle...
This paper presents a novel genetic algorithm for analog module placement. It is based on a generali...
This paper considers a new variant of the two-dimensional bin packing problem where each rectangle i...
We present a novel multi-population biased random-key genetic algorithm (BRKGA) for the 2D and 3D bi...
This paper presents an approach to the automatic place-ment of a combination of macro blocks and sta...