Hybrid genetic algorithms for constrained placement problems

When solving real-world problems, often the main task is to find a proper representation for the candidate solutions. Strings of elementary data types with standard genetic operators may tend to create infeasible individuals during the search because of the discrete and often constrained search space. This article introduces a generally applicable representation for 2D combinatorial placement and packing problems. Empirical results are presented for two constrained placement problems, the facility layout problem and the generation of VLSI macro-cell layouts. For multiobjective optimization problems, common approaches often deal with the different objectives in different phases and thus are unable to efficiently solve the global problem. Due to a tree structured genotype representation and hybrid, problem-specific operators, the proposed approach is able to deal with different constraints and objectives in one optimization step.

[1]  Peter Ross,et al.  A Study of Genetic Algorithm Hybrids for Facility Layout Problems , 1995, ICGA.

[2]  B. Kröger.  Guillotineable bin packing: A genetic approach , 1995 .

[3]  Andrew Kusiak,et al.  The facility layout problem , 1987 .

[4]  Hyung Rim Choi,et al.  A Genetic Algorithm Hybrid for Hierarchical Reactive Scheduling , 1997, ICGA.

[5]  D. E. Goldberg,et al.  Genetic Algorithms in Search, Optimization & Machine Learning , 1989 .

[6]  Hans-Paul Schwefel,et al.  Evolution and optimum seeking , 1995, Sixth-generation computer technology series.

[7]  Pinaki Mazumder,et al.  SAGA : a unification of the genetic algorithm with simulated annealing and its application to macro-cell placement , 1994, Proceedings of 7th International Conference on VLSI Design.

[8]  Dana S. Richards,et al.  Distributed genetic algorithms for the floorplan design problem , 1991, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[9]  Oliver Vornberger,et al.  Cutting Stock by Iterated Matching , 1995 .

[10]  Pinaki Mazumder,et al.  Macro-cell and module placement by genetic adaptive search with bitmap-represented chromosome , 1991, Integr..

[11]  Bernd Freisleben,et al.  A Genetic Local Search Approach to the Quadratic Assignment Problem , 1997, ICGA.

[12]  K. Tam,et al.  A hierarchical approach to the facility layout problem , 1991 .

[13]  Pinaki Mazumder,et al.  VLSI cell placement techniques , 1991, CSUR.

[14]  Thomas Bäck,et al.  An Overview of Evolutionary Algorithms for Parameter Optimization , 1993, Evolutionary Computation.

[15]  L. Darrell Whitley,et al.  The GENITOR Algorithm and Selection Pressure: Why Rank-Based Allocation of Reproductive Trials is Best , 1989, ICGA.

[16]  Roger L. Wainwright,et al.  Solving facility layout problems using genetic programming , 1996 .

[17]  Sadiq M. Sait,et al.  VLSI Physical Design Automation - Theory and Practice , 1995, Lecture Notes Series on Computing.

[18]  A. E. Eiben,et al.  Genetic algorithms with multi-parent recombination , 1994, PPSN.

[19]  James P. Cohoon,et al.  Genetic Placement , 1987, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[20]  Panos M. Pardalos,et al.  The Quadratic Assignment Problem: A Survey and Recent Developments , 1993, Quadratic Assignment and Related Problems.

[21]  Elwood S. Buffa,et al.  The Facilities Layout Problem in Perspective , 1966 .

[22]  Russell D. Meller,et al.  The facility layout problem: Recent and emerging trends and perspectives , 1996 .

[23]  K. Y. Tam,et al.  A simulated annealing algorithm for allocating space to manufacturing cells , 1992 .

[24]  C. Sechen,et al.  New algorithms for the placement and routing of macro cells , 1990, 1990 IEEE International Conference on Computer-Aided Design. Digest of Technical Papers.

[25]  D. Camp,et al.  A nonlinear optimization approach for solving facility layout problems , 1992 .

[26]  K. Dejong,et al.  An analysis of the behavior of a class of genetic adaptive systems , 1975 .

[27]  Thomas Lengauer,et al.  Robust and accurate hierarchical floorplanning with integrated global wiring , 1993, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[28]  Hidetoshi Onodera,et al.  Branch-and-bound placement for building block layout , 1991, 28th ACM/IEEE Design Automation Conference.

[29]  Peter J. Fleming,et al.  An Overview of Evolutionary Algorithms in Multiobjective Optimization , 1995, Evolutionary Computation.

[30]  Michael Upton,et al.  Integrated placement for mixed macro cell and standard cell designs , 1990, 27th ACM/IEEE Design Automation Conference.

[31]  Henrik Esbensen,et al.  A genetic algorithm for macro cell placement , 1992, Proceedings EURO-DAC '92: European Design Automation Conference.

[32]  Hugues Bersini,et al.  In Search of a Good Evolution-Optimization Crossover , 1992, PPSN.

[33]  Oliver Vornberger,et al.  An Adaptive Parallel Genetic Algorithm for VLSI-Layout Optimization , 1996, PPSN.

[34]  B. Freisleben,et al.  Genetic local search for the TSP: new results , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[35]  Thomas Lengauer,et al.  Combinatorial algorithms for integrated circuit layout , 1990, Applicable theory in computer science.

[36]  K. Y. Tam,et al.  Genetic algorithms, function optimization, and facility layout design , 1992 .

[37]  Naveed A. Sherwani,et al.  Algorithms for VLSI Physical Design Automation , 1999, Springer US.

[38]  Naveed A. Sherwani.  VLSI Physical Design Automation , 1995 .

[39]  David E. Goldberg,et al.  Genetic Algorithms with Sharing for Multimodalfunction Optimization , 1987, ICGA.

[40]  Markus Pape.  Chip Assembly mit topologischer Kompaktierung , 1995 .

[41]  H. Mühlenbein,et al.  Gene Pool Recombination in Genetic Algorithms , 1996 .

[42]  Larry J. Stockmeyer,et al.  Optimal Orientations of Cells in Slicing Floorplan Designs , 1984, Inf. Control..

[43]  Kenneth Alan De Jong,et al.  An analysis of the behavior of a class of genetic adaptive systems. , 1975 .

[44]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[45]  Heinz Mühlenbein,et al.  Parallel Genetic Algorithms, Population Genetics, and Combinatorial Optimization , 1989, Parallelism, Learning, Evolution.

[46]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.