### Abstract

Two methods of implementing computer programs for solving the shortest path problem are presented. By symbolic processing, a computer program generates another program or an address table which represents an optimal shortest path algorithm, in the sense that only nontrivial operations required for a given particular network structure are executed. The implementation methods presented are powerful when a network of fixed sparseness structure must be solved repeatedly with different numerical values.

Original language | English |
---|---|

Title of host publication | IEEE Trans Circuits Syst |

Pages | 752-758 |

Number of pages | 7 |

Volume | CAS-23 |

Edition | 12 |

Publication status | Published - 1976 Dec |

Externally published | Yes |

### Fingerprint

### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*IEEE Trans Circuits Syst*(12 ed., Vol. CAS-23, pp. 752-758)

**SPARSE MATRIX TECHNIQUES FOR THE SHORTEST PATH PROBLEM.** / Goto, Satoshi; Ohtsuki, Tatsuo; Yoshimura, Takeshi.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

*IEEE Trans Circuits Syst.*12 edn, vol. CAS-23, pp. 752-758.

}

TY - CHAP

T1 - SPARSE MATRIX TECHNIQUES FOR THE SHORTEST PATH PROBLEM.

AU - Goto, Satoshi

AU - Ohtsuki, Tatsuo

AU - Yoshimura, Takeshi

PY - 1976/12

Y1 - 1976/12

N2 - Two methods of implementing computer programs for solving the shortest path problem are presented. By symbolic processing, a computer program generates another program or an address table which represents an optimal shortest path algorithm, in the sense that only nontrivial operations required for a given particular network structure are executed. The implementation methods presented are powerful when a network of fixed sparseness structure must be solved repeatedly with different numerical values.

AB - Two methods of implementing computer programs for solving the shortest path problem are presented. By symbolic processing, a computer program generates another program or an address table which represents an optimal shortest path algorithm, in the sense that only nontrivial operations required for a given particular network structure are executed. The implementation methods presented are powerful when a network of fixed sparseness structure must be solved repeatedly with different numerical values.

UR - http://www.scopus.com/inward/record.url?scp=0017219893&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0017219893&partnerID=8YFLogxK

M3 - Chapter

VL - CAS-23

SP - 752

EP - 758

BT - IEEE Trans Circuits Syst

ER -