A genetic algorithm for the optimal sequential partitioning problem

Araki Hajime, Kaji Taichi, Yamamoto Masahito, Suzuki Keiji, Ohuchi Azuma

doi:10.1541/ieejeiss1987.120.2_215

Bibliographic Information

Other Title

遺伝的アルゴリズムによる最適系列分割問題の解法
イデンテキアルゴリズムニヨルサイテキケイレツブンカツモンダイノカイホウ

Search this article

Abstract

The optimal sequential partitioning problem is defined as the problem to find the minimum cost partition of the nodes of a directed acyclic graph into subsets of a given size, subject to the constraint that the prece-dence relationships among the elements are satisfied. The heuristic algorithm based on a tabu search for this problem has been proposed⁽²⁾. However, there is a tendency for the solutions obtained using the tabu search approach to be trapped in bad local optima in the parallel graphs with random costs of edges<br> In this paper we present the genetic algorithm for the optimal sequential partitioning problem. We developeffective two point partial order crossover satisfying sequential conditions, which preserve better block that has the larger sum of edge costs of block. In this crossover we introduce roulette selection method to escape local optima. We also assess the effectiveness of the developed algorithm. The results show that this proposed algorithm outperforms, in terms of solution quality, any other algorithm using tabu search.

Journal

IEEJ Transactions on Electronics, Information and Systems

IEEJ Transactions on Electronics, Information and Systems 120 (2), 215-221, 2000

The Institute of Electrical Engineers of Japan

Keywords

Details 詳細情報について

Export