## Advanced Search Techniques For Circuit Partitioning (1994)

Venue: | In DIMACS Series in Discrete Mathematics and Theoretical Computer Science |

Citations: | 15 - 3 self |

### BibTeX

@INPROCEEDINGS{Areibi94advancedsearch,

author = {Shawki Areibi and Anthony Vannelli},

title = {Advanced Search Techniques For Circuit Partitioning},

booktitle = {In DIMACS Series in Discrete Mathematics and Theoretical Computer Science},

year = {1994},

pages = {77--98},

publisher = {AMS}

}

### Years of Citing Articles

### OpenURL

### Abstract

. Most real world problems especially circuit layout and VLSI design are too complex for any single processing technique to solve in isolation. Stochastic, adaptive and local search approaches have strengths and weaknesses and should be viewed not as competing models but as complimentary ones. This paper describes the application of a combined Tabu Search [1] and Genetic Algorithm heuristic to guide an efficient interchange algorithm to explore and exploit the solution space of a hypergraph partitioning problem. Results obtained indicate, that the generated solutions and running time of this hybrid are superior to results obtained from a combined eigenvector and node interchange method [11]. 1. Introduction In the combinatorial sense, the layout problem is a constrained optimization problem. We are given a description of a circuit (usually called a netlist) which is a description of switching elements and their connecting wires. We seek an assignment of geometric coordinates of the ci...

### Citations

2827 |
Adaptation in natural and artificial systems
- Holland
- 1975
(Show Context)
Citation Context ...gh probability for leading to good solutions [21]. The algorithms are called Genetic because the manipulation of possible solutions resembles the mechanics of natural selection. Introduced by Holland =-=[13]-=- in 1975, these algorithms are based on the notion of propagating new solutions from parent solutions, employing mechanisms modeled after those currently believed to apply in genetics. The best offspr... |

1966 |
Genetic Algorithms + Data Structure = Evolution Programs
- Michalewicz
- 1992
(Show Context)
Citation Context ... use group-number encoding where the j-th integer i j 2 f1; : : : ; kg indicates the group number assigned to object j. This representation scheme creates a possibility of applying standard operators =-=[16]-=-. However an offspring may contain less than k groups; moreover, an offspring of two parents, both representing feasible solutions may be infeasible, since the constraint of having equal number of mod... |

1809 |
Genetic algorithms in search, optimization, and machine learning
- Goldberg
(Show Context)
Citation Context ...completely evaluating the solution. The selection method used in the second implementation Table 5 is a deterministic method rather than the stochastic method based on roulette wheel parent selection =-=[9]-=-. Table 6 presents solutions (partitions) based on the second representation method (permutation with separators). Since all solutions that evolve using this representation scheme are feasible, the co... |

473 |
Tabu search - part i
- Glover
- 1989
(Show Context)
Citation Context ...ess. 2.1.3. Intermediate and Long Term Memory. Intermediate and long term memory functions are employed within Tabu Search to achieve regional intensification and global diversification of the search =-=[7, 8]. Combined with the -=-short term memory functions, intermediate and long term memory functions provide an interplay between "exploitation" and "exploration" of the solution space [7] (fine tuned search ... |

427 |
Mattheyses, A linear-time heuristic for improving network partitions
- Fiduccia, M
- 1982
(Show Context)
Citation Context ...he tabu lists are activated only when the algorithm hits the first local minima. To achieve that without cycling to previous solutions, the interchange method using a certain number of passes is used =-=[6]-=-. Once local minima is reached the tabu lists are activated and the Tabu Search algorithm resumes exploration for better solutions through the short term memory. ADVANCED SEARCH TECHNIQUES FOR CIRCUIT... |

143 |
Lower bounds for the partitioning of graphs
- Donath, Hoffman
- 1973
(Show Context)
Citation Context ...nding lower bounds on the number of edges cut in a k-partition. Table 2 shows the lower bounds obtained on the number of cut nets for the different benchmarks using the Donath-Hoffman bounds technique=-=[5]-=-. Initial Solutions. Tables 3, 4, 5 and 6 present quality of partitions obtained for 2,4 and 6 blocks for different circuits using the eigenvector approach and Genetic Algorithm respectively. The CPU ... |

132 |
Using Tabu Search Techniques for Graph Coloring
- Hertz, Werra
- 1987
(Show Context)
Citation Context ... ideas it has been extremely efficient in getting almost optimal solutions for many types of difficult combinatorial optimization problems ranging from graph partitioning [1] [2] [20], graph coloring =-=[12], to quadratic assig-=-nment problems [19]. Figure1 shows the basic components of Tabu Search. These Tabu Search Main Components Short Term Mem "Prevent Cycling" Aspiration "Backtracking" Long / Medium T... |

117 |
Multi-Way Network Partitioning
- Sanchis
- 1989
(Show Context)
Citation Context ...gence rate of all Methods ADVANCED SEARCH TECHNIQUES FOR CIRCUIT PARTITIONING 21 5. Conclusion and Future Work In this paper, we have introduced the use of the Tabu Search method to guide the Sanchis =-=[18]-=- Multi-way interchange algorithm and improve the initial starting partitions generated by a Genetic Algorithm. The combination of Tabu Search and Genetic Algorithm as seen in the last section gives ri... |

70 |
An algorithm for partitioning the nodes of a graph
- Barnes
(Show Context)
Citation Context ....2) s.t. (i) Module placement constraints: n b X k=1 x ik = 1; 8 i = 1; 2; : : : ; nm (ii) Block size constraints nm X i=1 x iksnm n b ; 8 k = 1; 2; : : : ; n b x ik 2 f0; 1g; 1sisnm ; 1sksn b Barnes =-=[3]-=- developed a polynomial time heuristic for approximating the above 0-1 quadratic transportation problem. The heuristic is based on approximating the netlist or hypergraph by a weighted graph G, that t... |

66 | A Parallel Genetic Algorithm for the Set Partitioning Problem
- Levine
- 1994
(Show Context)
Citation Context ...c Algorithms have recently received much attention as a robust stochastic searching algorithm for various optimization problems, ranging from multiprocessor scheduling [14], set partitioning problems =-=[15]-=- to quadratic assignment problems [4]. As an optimization technique, Genetic Algorithms simultaneously examine and manipulate a set of possible solutions. Each candidate solution is represented by a s... |

15 |
search—Part II
- “Tabu
- 1990
(Show Context)
Citation Context ...ess. 2.1.3. Intermediate and Long Term Memory. Intermediate and long term memory functions are employed within Tabu Search to achieve regional intensification and global diversification of the search =-=[7, 8]. Combined with the -=-short term memory functions, intermediate and long term memory functions provide an interplay between "exploitation" and "exploration" of the solution space [7] (fine tuned search ... |

10 |
Efficient multiprocessor scheduling based on genetic algorithms
- Hou, Hong, et al.
- 1990
(Show Context)
Citation Context ...istics of Genetic Search. Genetic Algorithms have recently received much attention as a robust stochastic searching algorithm for various optimization problems, ranging from multiprocessor scheduling =-=[14]-=-, set partitioning problems [15] to quadratic assignment problems [4]. As an optimization technique, Genetic Algorithms simultaneously examine and manipulate a set of possible solutions. Each candidat... |

9 |
A parallel heuristic for quadratic assignment problems
- Huntley, Brown
- 1991
(Show Context)
Citation Context ...ch attention as a robust stochastic searching algorithm for various optimization problems, ranging from multiprocessor scheduling [14], set partitioning problems [15] to quadratic assignment problems =-=[4]-=-. As an optimization technique, Genetic Algorithms simultaneously examine and manipulate a set of possible solutions. Each candidate solution is represented by a string of symbols called a chromosome.... |

8 |
A Combined Eigenvector Tabu Search Approach for Circuit Partitioning
- Areibi, Vannelli
- 1993
(Show Context)
Citation Context ...aptive and local search approaches have strengths and weaknesses and should be viewed not as competing models but as complimentary ones. This paper describes the application of a combined Tabu Search =-=[1]-=- and Genetic Algorithm heuristic to guide an efficient interchange algorithm to explore and exploit the solution space of a hypergraph partitioning problem. Results obtained indicate, that the generat... |

6 |
An Efficient Eigenvector and Node Interchange Approach for Finding Netlist Partitions
- Hadley, Mark, et al.
- 1992
(Show Context)
Citation Context ... partitioning problem. Results obtained indicate, that the generated solutions and running time of this hybrid are superior to results obtained from a combined eigenvector and node interchange method =-=[11]-=-. 1. Introduction In the combinatorial sense, the layout problem is a constrained optimization problem. We are given a description of a circuit (usually called a netlist) which is a description of swi... |

6 |
Genetic Algorithmic framework for process design and optimization
- Adroulakis, Venkatasubramanian, et al.
- 1991
(Show Context)
Citation Context ...ms. Genetic Algorithms (GA's) are a class of optimization algorithms that seek improved performance by sampling areas of the parameter space that have a high probability for leading to good solutions =-=[21]-=-. The algorithms are called Genetic because the manipulation of possible solutions resembles the mechanics of natural selection. Introduced by Holland [13] in 1975, these algorithms are based on the n... |

2 |
Physical Design Workshop 1987
- Roberts, Preas
- 1987
(Show Context)
Citation Context ...ithm are presented in Table 1. Chip1 circuit is taken from the work of Fidduccia & Matheyses [6]. Primary1, Primary2 and BIO are taken from the MCNC gate array and standard cell test suite benchmarks =-=[17]-=-. As seen in the table these netlists(hypergraphs) vary in size from 300 to 6000 nodes and 300 to 5000 nets. The quality of a netlist partition can be determined by finding lower bounds on the number ... |

2 |
Tabu Search Applied To The Quadratic Assignment Problem
- Skorun-Kapov
- 1990
(Show Context)
Citation Context ...in getting almost optimal solutions for many types of difficult combinatorial optimization problems ranging from graph partitioning [1] [2] [20], graph coloring [12], to quadratic assignment problems =-=[19]. Figure1 shows the -=-basic components of Tabu Search. These Tabu Search Main Components Short Term Mem "Prevent Cycling" Aspiration "Backtracking" Long / Medium Term Memory Diversify Search Intensify S... |

1 |
Partitioning Using A Tabu Search Approach
- Circuit
- 1993
(Show Context)
Citation Context ...mization. Based on simple ideas it has been extremely efficient in getting almost optimal solutions for many types of difficult combinatorial optimization problems ranging from graph partitioning [1] =-=[2] [20], graph co-=-loring [12], to quadratic assignment problems [19]. Figure1 shows the basic components of Tabu Search. These Tabu Search Main Components Short Term Mem "Prevent Cycling" Aspiration "Bac... |

1 |
Intelligent Hybrid Systems, To Appear
- Goonatilake, Khebbal
- 1992
(Show Context)
Citation Context ...id system is. Much of the problem lies in the different interpretation of functionality and architecture of these systems. As shown in Figure 6, we can classify hybrid systems in the following manner =-=[10]-=-: ffl Intercommunicating hybrids are independent, self contained, processing modules that exchange information, and perform separate functions to generate solutions. Communication and synchronization ... |

1 |
An Efficient Tabu Search Algorithm
- Tao, Zhao, et al.
- 1991
(Show Context)
Citation Context ...tion. Based on simple ideas it has been extremely efficient in getting almost optimal solutions for many types of difficult combinatorial optimization problems ranging from graph partitioning [1] [2] =-=[20], graph colorin-=-g [12], to quadratic assignment problems [19]. Figure1 shows the basic components of Tabu Search. These Tabu Search Main Components Short Term Mem "Prevent Cycling" Aspiration "Backtrac... |