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**A parallel heuristic for quadratic assignment problems.**
*(English)*
Zbl 0723.90044

Summary: The quadratic assignment problem represents an important class of problems with applications as diverse as facility layout and data analysis. The importance of these applications coupled with the fact that the quadratic assignment problem is NP-hard has encouraged the development of heuristics because optimal seeking procedures have been restricted to very small versions of the problem. This paper describes a new parallel heuristic, SAGA, for the quadratic assignment problem. SAGA is a cascaded hybrid of a genetic algorithm and simulated annealing. In addition to details regarding SAGA and its implementation, this paper also describes the performance of SAGA on two standard problems taken from the literature. The results from these problems show SAGA to be superior to the most commonly employed heuristic in solution quality, and for large problems it is also superior in solution time.

### MSC:

90B80 | Discrete location and assignment |

90C27 | Combinatorial optimization |

65Y05 | Parallel numerical computation |

90-08 | Computational methods for problems pertaining to operations research and mathematical programming |

68W15 | Distributed algorithms |

90C20 | Quadratic programming |

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\textit{C. L. Huntley} and \textit{D. E. Brown}, Comput. Oper. Res. 18, No. 3, 275--289 (1991; Zbl 0723.90044)

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