1,721,142 research outputs found
A coloured Petri net model for automated storage and retrieval systems serviced by rail-guided vehicles: A control perspective
No full textAn Automated Storage and Retrieval System (AS/RS) automatically stores incoming material and retrieves stored parts with no direct human handling. This paper proposes a modular and unified modelling framework for heterogeneous automated storage and retrieval systems, comprising rail guided vehicles and narrow aisle cranes. We employ coloured timed Petri nets, representing a concise and computationally efficient tool for modelling the system dynamic behaviour, particularly suitable for real-time control implementation. Indeed, the model can be utilized in a discrete event simulation to apply control policies in order to solve scheduling problems, as well as to avoid deadlock and collision occurrences
A Generalized Stochastic Petri Net Model for Management of Distributed Manufacturing Systems
No full textA Distributed Manufacturing System (DMS) is a collection of independent companies possessing complementary skills and integrated with transportation and storage systems. This paper deals with the issues of modeling and managing a DMS. The system is modeled as a timed discrete event dynamical system by generalized stochastic Petri nets. Moreover, two well known broad policies are considered to manage the DMS: make-to-stock and make-to-order. In order to compare the two management techniques and to show the effectiveness of each method, a case study is presente
Performance-Based Comparison of Control Policies for Automated Storage and Retrieval Systems Modelled by Coloured Petri Nets
No full textThe industrial manufacturing environment is nowadays characterized by fierce global competition, rapid market changes and short product life cycles. Such a complex scenario originated a vast demand for sophisticated techniques guaranteeing adequate planning and control of warehouses. A widely used solution is to adopt Automated Storage and Retrieval Systems (AS/RSs). A typical AS/RS comprises a number of parallel aisles with storage racks, serviced by automated stacker cranes and rail guided vehicles. This paper compares several management strategies addressing the system operational control, i.e., dealing with the AS/RS real time behaviour. A common coloured timed Petri net models the system and the controlled AS/RS operation is highlighted by way of several discrete event simulations carried out in the Matlab-Stateflow software environment. The proposed control policies are compared and discussed on the basis of appropriate performance indices
A Timed Petri Nets Model for Performance Evaluation of Intermodal Freight Transport Terminals
Full text linkThis paper presents a general modeling framework for Intermodal Freight Transport Terminals (IFTTs). The model allows simulating and evaluating the performance of such key elements of the intermodal transportation chain. Hence, it may be used by the decision maker to identify the IFTT bottlenecks, as well as to test different solutions to improve the IFTT dynamics. The proposed modeling framework is modular and based on timed Petri Nets (PNs), where places represent resources and capacities or conditions, transitions model inputs, flows, and activities into the terminal and tokens are intermodal transport units or the means on which they are transported. The model is able to represent the different types of existing IFTTs. Its effectiveness is tested first on an example from the literature and then on a real case study, the railroad inland terminal of a leading Italian intermodal logistics company, showing its ease of application. In the real case study, using the proposed formalism we test the as-is IFTT performance and evaluate alternative possible to-be improvements in order to identify and eliminate emerging criticalities in the terminal dynamics
A stochastic cross-efficiency data envelopment analysis approach for supplier selection under uncertainty
No full textThis paper addresses one of the key objectives of the supply chain strategic design phase, that is, the optimal selection of suppliers. A methodology for supplier selection under uncertainty is proposed, integrating the cross-efficiency data envelopment analysis (DEA) and Monte Carlo approach. The combination of these two techniques allows overcoming the deterministic feature of the classical cross-efficiency DEA approach. Moreover, we define an indicator of the robustness of the determined supplier ranking. The technique is able to manage the supplier selection problem considering nondeterministic input and output data. It allows the evaluation of suppliers under uncertainty, a particularly significant circumstance for the assessment of potential suppliers. The novel approach helps buyers in choosing the right partners under uncertainty and ranking suppliers upon a multiple sourcing strategy, even when considering complex evaluations with a high number of suppliers and many input and output criteria
A cross-efficiency fuzzy Data Envelopment Analysis technique for performance evaluation of Decision Making Units under uncertainty
No full textThe paper presents a novel cross-efficiency fuzzy Data Envelopment Analysis (DEA) technique for evaluating different elements (Decision Making Units or DMUs) under uncertainty. In order to evaluate the performance of several DMUs while dealing with uncertain input and output data, the presented technique employs triangular fuzzy numbers. A fuzzy triangular efficiency is associated to each DMU through a cross evaluation obtained by a compromise between suitably chosen objectives. Results are then defuzzified to provide a ranking of the DMUs. The proposed method is applied to the performance evaluation of healthcare systems in a region of Southern Italy. The DMU data uncertainty derives from ongoing reforms and the reported assessment is conducted firstly in order to evaluate and rank the efficiency of the considered healthcare systems, and subsequently to assess the evolution of the performance of one of the most affected among these DMUs by the reform plans. The case study demonstrates the model ease of application, its discriminative power among DMUs when compared to a more classical fuzzy DEA approach, and the usefulness in planning and validating targeted reforms in the case of healthcare systems
A hierarchical vendor selection optimization technique for multiple sourcing
No full textThe paper addresses a crucial objective of the strategic function of purchasing in supply chains, i.e., vendor rating, proposing a hierarchical model for supplier business intelligence. A three-level optimization process for supplier selection in a multiple sourcing strategy context is proposed. First, the Data Envelopment Analysis, the most widespread method for supplier selection, is used to evaluate the efficiency of suppliers. Second, the well-known Analytic Hierarchy Process is applied to rank the efficient suppliers given by the previous step. Third, a linear programming problem is solved to find the quantities to order from each efficient supplier. We show the model effectiveness on a simulated case study of a C class component
Logistics 4.0: A Matheuristics for the Integrated Vehicle Routing and Container Loading Problem
No full textThe increasing demand for freight transport requires logistic companies to improve their competitiveness by ensuring high service levels at limited costs. This paper investigates the problem of defining delivery plans with the aim to support logistic companies in reducing planning times and freight delivery costs. In delivery planning, given a set of delivery requests, both the routes and load configurations of Transport Units (TUs) are to be established. In the literature, this problem is defined as Three-dimensional Loading Capacitated Vehicle Routing Problem with Time Windows (3LCVRPTW). However, these problems are generally tackled separately and referred to as the vehicle routing problem and the container loading problem, respectively. Moreover, only a few contributions present solution approaches for real logistic systems, and these methods are mainly based on heuristics. In this work, we define a novel matheuristic algorithm for the integrated solution of the vehicle routing problem and container loading problem. The proposed method is suitable for real logistic applications and combines the advantages of exact solutions with the rapidity of heuristics. The approach aims at minimizing the total travel costs and the clients' time windows violations in the routes' definition, while optimizing the configuration of the cargo inside each TU. The developed matheuristic algorithm is tested both on a well-known literature benchmark and on a real dataset provided by the Italian company Elettric80. The obtained results show that the proposed method succeeds in determining in a short computational time both feasible routes and loading plans, minimizing the related costs while fulfilling logistics constraints
Efficient Resource Planning of Intermodal Terminals under Uncertainty
No full textThis paper presents a decision support tool for the efficient resource planning and management of intermodal terminals under uncertainty, allowing to address the planning issue under imprecise or uncertain data (e.g., estimates on flows, resource utilization, operating conditions). The procedure consists of three steps: 1) the definition of a Timed Petri Net model of the terminal; 2) the computation of suitable performance indices to evaluate whether the current configuration is able to cope with a foreseen increase in the freight flows; 3) in the case of not satisfactory values of the indices at the previous step, the simulation of alternative planning solutions and the detection of the most efficient one via a cross efficiency fuzzy Data Envelopment Analysis technique. In order to test its effectiveness, the procedure is applied to a real case study. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved
A signal timing plan formulation for urban traffic control
No full textThis paper addresses urban traffic control using an optimization model for signalized areas. The paper modifies and extends a discrete time model for urban traffic networks proposed in the related literature to take into account some real aspects of traffic. The model is embedded in a real time controller that solves an optimization problem from the knowledge of some measurable inputs. Hence, the controller determines the signal timing plan on the basis of technical, physical, and operational constraints. The actuated control strategy is applied to a case study with severe traffic congestion, showing the effectiveness of the technique
- …
