### 抄録

We formulate an assignment problem-solving framework called singleobject resource allocation with preferential order (SORA/PO) to incorporate values of resources and individual preferences into assignment problems. We then devise methods to find semi-optimal solutions for SORA/PO problems. The assignment, or resource allocation, problem is a fundamental problem-solving framework used in a variety of recent network and distributed applications. However, it is a combinatorial problem and has a high computational cost to find the optimal solution. Furthermore, SORA/PO problems require solutions in which participating agents express no or few dissatisfactions on the basis of the relationship between relative values and the agents’ preference orders. The algorithms described herein can efficiently find a semi-optimal solution that is satisfactory to almost all agents even though its sum of values is close to that of the optimal solution. We experimentally evaluate our methods and the derived solutions by comparing them with tho optimal solutions calculated by CPLEX. We also compare the running times for the solution obtained by these methods.

元の言語 | English |
---|---|

ホスト出版物のタイトル | Agent and Multi-Agent Systems: Technology and Applications - 10th KES International Conference, KES-AMSTA 2016, Proceedings |

出版者 | Springer Science and Business Media Deutschland GmbH |

ページ | 33-44 |

ページ数 | 12 |

巻 | 58 |

ISBN（印刷物） | 9783319398822 |

DOI | |

出版物ステータス | Published - 2016 |

イベント | 10th KES International Conference on Agent and Multi-Agent Systems: Technology and Applications, KES-AMSTA 2016 - Puerto de la Cruz, Tenerife, Spain 継続期間: 2016 6 15 → 2016 6 17 |

### 出版物シリーズ

名前 | Smart Innovation, Systems and Technologies |
---|---|

巻 | 58 |

ISSN（印刷物） | 21903018 |

ISSN（電子版） | 21903026 |

### Other

Other | 10th KES International Conference on Agent and Multi-Agent Systems: Technology and Applications, KES-AMSTA 2016 |
---|---|

国 | Spain |

市 | Puerto de la Cruz, Tenerife |

期間 | 16/6/15 → 16/6/17 |

### Fingerprint

### ASJC Scopus subject areas

- Computer Science(all)
- Decision Sciences(all)

### これを引用

*Agent and Multi-Agent Systems: Technology and Applications - 10th KES International Conference, KES-AMSTA 2016, Proceedings*(巻 58, pp. 33-44). (Smart Innovation, Systems and Technologies; 巻数 58). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-39883-9_3

**Assignment problem with preference and an efficient solution method without dissatisfaction.** / Saito, Kengo; Sugawara, Toshiharu.

研究成果: Conference contribution

*Agent and Multi-Agent Systems: Technology and Applications - 10th KES International Conference, KES-AMSTA 2016, Proceedings.*巻. 58, Smart Innovation, Systems and Technologies, 巻. 58, Springer Science and Business Media Deutschland GmbH, pp. 33-44, 10th KES International Conference on Agent and Multi-Agent Systems: Technology and Applications, KES-AMSTA 2016, Puerto de la Cruz, Tenerife, Spain, 16/6/15. https://doi.org/10.1007/978-3-319-39883-9_3

}

TY - GEN

T1 - Assignment problem with preference and an efficient solution method without dissatisfaction

AU - Saito, Kengo

AU - Sugawara, Toshiharu

PY - 2016

Y1 - 2016

N2 - We formulate an assignment problem-solving framework called singleobject resource allocation with preferential order (SORA/PO) to incorporate values of resources and individual preferences into assignment problems. We then devise methods to find semi-optimal solutions for SORA/PO problems. The assignment, or resource allocation, problem is a fundamental problem-solving framework used in a variety of recent network and distributed applications. However, it is a combinatorial problem and has a high computational cost to find the optimal solution. Furthermore, SORA/PO problems require solutions in which participating agents express no or few dissatisfactions on the basis of the relationship between relative values and the agents’ preference orders. The algorithms described herein can efficiently find a semi-optimal solution that is satisfactory to almost all agents even though its sum of values is close to that of the optimal solution. We experimentally evaluate our methods and the derived solutions by comparing them with tho optimal solutions calculated by CPLEX. We also compare the running times for the solution obtained by these methods.

AB - We formulate an assignment problem-solving framework called singleobject resource allocation with preferential order (SORA/PO) to incorporate values of resources and individual preferences into assignment problems. We then devise methods to find semi-optimal solutions for SORA/PO problems. The assignment, or resource allocation, problem is a fundamental problem-solving framework used in a variety of recent network and distributed applications. However, it is a combinatorial problem and has a high computational cost to find the optimal solution. Furthermore, SORA/PO problems require solutions in which participating agents express no or few dissatisfactions on the basis of the relationship between relative values and the agents’ preference orders. The algorithms described herein can efficiently find a semi-optimal solution that is satisfactory to almost all agents even though its sum of values is close to that of the optimal solution. We experimentally evaluate our methods and the derived solutions by comparing them with tho optimal solutions calculated by CPLEX. We also compare the running times for the solution obtained by these methods.

KW - Assignment problem

KW - Cardinal and ordinal values

KW - Preference

KW - Resource allocation problem

UR - http://www.scopus.com/inward/record.url?scp=84979022767&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84979022767&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-39883-9_3

DO - 10.1007/978-3-319-39883-9_3

M3 - Conference contribution

AN - SCOPUS:84979022767

SN - 9783319398822

VL - 58

T3 - Smart Innovation, Systems and Technologies

SP - 33

EP - 44

BT - Agent and Multi-Agent Systems: Technology and Applications - 10th KES International Conference, KES-AMSTA 2016, Proceedings

PB - Springer Science and Business Media Deutschland GmbH

ER -