Worldwide competition originated the development of integrated supply chains (SCs) that are distributed manufacturing systems integrating international logistics and information technologies with production. This paper develops a decision-making model based on discrete consensus in order to assign tasks to each actor of the SC at the operational level. In particular, some actors of the SC generate tasks that other actors, localized in a downstream stage, have to complete. We provide a novel distributed algorithm that aims to minimize the task costs assuming that each actor can perform a subset of the available tasks and can communicate with a subset of actors. In order to show the effectiveness of the distributed algorithm, a case study is considered. The problem is formalized as a distributed consensus algorithm, i.e., as a procedure using which the agents of the SC can exchange messages and update autonomously and iteratively their assigned tasks. Some results prove that the convergence to a task assignment consensus is reached in finite time and a stopping criterion is provided
A Distributed Consensus Algorithm for Task Allocation in Supply Chain Management / Fanti, M. P.; Mangini, A. M.; Ukovich, W.. - ELETTRONICO. - 45:6(2012), pp. 566-571. (Intervento presentato al convegno 14th IFAC Symposium on Information Control Problems in Manufacturing, INCOM'12 tenutosi a Bucharest, Romania nel May 23-25, 2012) [10.3182/20120523-3-RO-2023.00085].
A Distributed Consensus Algorithm for Task Allocation in Supply Chain Management
M. P. Fanti;A. M. Mangini;
2012-01-01
Abstract
Worldwide competition originated the development of integrated supply chains (SCs) that are distributed manufacturing systems integrating international logistics and information technologies with production. This paper develops a decision-making model based on discrete consensus in order to assign tasks to each actor of the SC at the operational level. In particular, some actors of the SC generate tasks that other actors, localized in a downstream stage, have to complete. We provide a novel distributed algorithm that aims to minimize the task costs assuming that each actor can perform a subset of the available tasks and can communicate with a subset of actors. In order to show the effectiveness of the distributed algorithm, a case study is considered. The problem is formalized as a distributed consensus algorithm, i.e., as a procedure using which the agents of the SC can exchange messages and update autonomously and iteratively their assigned tasks. Some results prove that the convergence to a task assignment consensus is reached in finite time and a stopping criterion is providedI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.