A Distributed Consensus Algorithm for Task Allocation in Supply Chain Management

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 Fault Detection Approach for Industrial Systems

The paper addresses the fault detection problem for large discrete event systems that can be modelled by a set of interacting Petri Net (PN) modules. Each system module is monitored by a PN diagnoser that has local information on the module structure and shares information by some places that are coupled with the other modules of the system. Each diagnoser works on-line: it waits for the firing of an observable transition and employs an algorithm based on the definition of some integer linear programming problems to decide whether the system behaviour is normal or exhibits some possible faults. A case study presented in the related literature shows the distributed fault detection strategy and points out the efficiency of the proposed approach

Fleet sizing for electric car sharing system via closed queueing networks

This paper addresses the problem of determining the optimal fleet size of electric car sharing systems. We model the system as a Discrete Event System in a closed queueing network framework considering the specific requirements of the electric vehicle utilization. Hence, we describe the asymptotic behavior of the vehicles and develop an optimization problem for maximizing the system revenue by determining the optimal fleet size. The large-scale of real-world systems results in computational difficulties in obtaining the exact solution, and so an approximate formulation is provided. Some numerical results illustrate and validate the solution method. \ua9 2014 IEEE

An Improved Freeway Traffic Model in a First Order Hybrid Petri Net Framework

The paper presents a model for traffic state estimation and management of the freeways. The model is based on First-Order Hybrid Petri Nets (FOHPNs), a hybrid Petri net formalism including continuous places holding fluid, discrete places containing a non-negative integer number of tokens and transitions, which are either discrete or continuous. The paper improves a previous model in order to suitably describe the dynamics of the freeway traffic flow. To this aim we modify the dynamics of the FOHPN and we allow updating the transition firing speed as a function of the markings modeling the freeway traffic. The use of FOHPNs offers several significant advantages with respect to the model existing in the related literature: the graphical feature enables an easy modular modeling approach and the mathematical aspects efficiently allow simulating and optimizing the system. The obtained model is a linear discrete-time, time-varying state variable model and is suitable to describe a hybrid system such as a freeway subject to unpredictable events (i.e., accidents or bottlenecks). The effectiveness of the FOHPN formalism is shown by applying the proposed modeling technique to a stretch of a freeway in the North-East of Italy. Some simulation studies illustrate how the proposed model is able to provide a support to analyze the strategies to react to accidents and lane blockings

A framework for the distributed management of charging operations

This paper proposes a solution for the distributed dynamic assignment of a set of electric vehicles to a network of charging stations. Drivers of the electric vehicles and charging stations exchange messages using a communication protocol. Drivers of the vehicles send requests for the charging of their own vehicle in prefixed timeslots; charging stations perform a series of distributed optimizations in order to reach a common assignment of the vehicles needing to recharge and communicate the reached assignment to the drivers. The optimization problem is solved using some distributed multi-agent assignment algorithms: the stations reach a consensus solving some local integer linear programming problems. \ua9 2014 IEEE