Resource Allocation, Agent-based Negotiation, Decision Making
This paper addresses energy-aware room allocation management where the system aims to satisfy individuals’ needs as much as possible while concerning total energy consumption in a building. In the problem, there are a several rooms having varied settings resulting in different energy consumption. The main objective of the system is not only finding the right allocations for user’s need, but also minimizing energy consumption. However, the users of the system may have conflicting preferences over the rooms to be allocated for them. This paper pursues how the system can increase user satisfaction while achieving its goals. For that purpose, an adaptation of the mediated single text negotiation model is introduced. The proposal seeks to guarantee an upper bound on energy consumption by pruning the negotiation space via a genetic algorithm, and to take advantage of the negotiation for increasing user satisfaction. Experiments suggest that the adaptations improve the performance.
Bibtex info
@inproceedings{esparcia_negotiation_2013,
address = {Berlin, Heidelberg},
title = {A {Negotiation} {Approach} for {Energy}-{Aware} {Room} {Allocation} {Systems}},
isbn = {978-3-642-38061-7},
abstract = {This paper addresses energy-aware room allocation management where the system aims to satisfy individuals' needs as much as possible while concerning total energy consumption in a building. In the problem, there are a several rooms having varied settings resulting in different energy consumption. The main objective of the system is not only finding the right allocations for user's need, but also minimizing energy consumption. However, the users of the system may have conflicting preferences over the rooms to be allocated for them. This paper pursues how the system can increase user satisfaction while achieving its goals. For that purpose, an adaptation of the mediated single text negotiation model is introduced. The proposal seeks to guarantee an upper bound on energy consumption by pruning the negotiation space via a genetic algorithm, and to take advantage of the negotiation for increasing user satisfaction. Experiments suggest that the adaptations improve the performance.},
booktitle = {Highlights on {Practical} {Applications} of {Agents} and {Multi}-{Agent} {Systems}},
publisher = {Springer Berlin Heidelberg},
author = {Esparcia, Sergio and Sánchez-Anguix, Victor and Aydoğan, Reyhan},
editor = {Corchado, Juan M. and Bajo, Javier and Kozlak, Jaroslaw and Pawlewski, Pawel and Molina, Jose M. and Julian, Vicente and Silveira, Ricardo Azambuja and Unland, Rainer and Giroux, Sylvain},
year = {2013},
pages = {280--291},
}