Due to the spread of the social engagement paradigm, several companies are asking people to perform tasks in exchange for a reward. The advantages of this business model are savings in economic and environmental terms. In previous works, it has been proved that the problem of finding the minimum amount of reward such that all tasks are performed is difficult to solve, even for medium-size realistic instances (if more than one type of person is considered). In this paper, we propose a customized version of the progressive hedging algorithm that is able to provide good solutions for large realistic instances. The proposed method reaches the goal of defining a procedure that can be used in real environments.
|Titolo:||A Progressive Hedging Method for the Optimization of Social Engagement and Opportunistic IoT Problems|
|Data di pubblicazione:||2019|
|Digital Object Identifier (DOI):||10.1016/j.ejor.2019.02.052|
|Appare nelle tipologie:||1.1 Articolo in rivista|