TY - GEN
T1 - Assignment problem with preference and an efficient solution method without dissatisfaction
AU - Saito, Kengo
AU - Sugawara, Toshiharu
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
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
T3 - Smart Innovation, Systems and Technologies
SP - 33
EP - 44
BT - Agent and Multi-Agent Systems
A2 - Jezic, Gordan
A2 - Jain, Lakhmi C.
A2 - Chen-Burger, Yun-Heh Jessica
A2 - Howlett, Robert J.
A2 - Jain, Lakhmi C.
A2 - Jain, Lakhmi C.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 10th KES International Conference on Agent and Multi-Agent Systems: Technology and Applications, KES-AMSTA 2016
Y2 - 15 June 2016 through 17 June 2016
ER -