Title: Modelling and performance analysis of smart waste collection system: a Petri nets and discrete event simulation approach
Authors: Taha Benarbia; Abdel Moumen Darcherif; Daniel Jian Sun
Addresses: University of Oran 2 IMSI, BP 1015 El M'naouer 31000 Oran, Algeria; Institute for Transport Planning and Systems IVT, ETH, Stefano-Franscini-Platz 5 8093 Zürich, Schweize, Switzerland ' ECAM-EPMI, Graduate School of Engineering, 13. Bd de l'Hautil 95092 Cergy-Pontoise Cedex, France ' Smart City and Intelligent Transportation Inter-Disciplinary Center, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Shanghai 200240, China; State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Abstract: With the recent development of smart cities all over the world, many new performance services have been developed, including smart mobility, energy and waste collection. In general, waste collection operators face the challenge of routing management, so as to reduce the costs of transportation and energy consumption. This paper proposes a waste collection strategy model based on real time inventory control of the vehicles' routing problem, with stochastic Petri nets (PN). The developed model and simulations show the capability of using PN models to predict the critical situations, analyse collection strategy efficiency, and improve performance. Results from the numerical example indicate that the overall vehicle travel distance for waste collection has been significantly reduced by estimating the exact moment to launch the collection service, as well as resolves conflict between vehicles during the collection. Simulation scenarios were introduced to assess the real time impact by monitoring the collection process.
Keywords: smart waste collection; stochastic Petri nets; discrete event simulation; decision making; vehicle routing problem.
International Journal of Decision Support Systems, 2019 Vol.4 No.1, pp.18 - 40
Received: 12 Nov 2018
Accepted: 22 Jun 2019
Published online: 18 Nov 2019 *