Oil-derivatives pipeline logistics using discrete-event simulation

The management of oil-product pipelines represents a critical task in the daily operation of petroleum supply chains. Efficient computational tools are needed to perform this activity in a reliable and costeffective manner. This work presents a novel discrete event simulation system developed on Arena® for the detailed scheduling of a multiproduct pipeline consisting of a sequence of pipes that connect a single input station to several receiving terminals. The pipeline is modeled as a non-traditional multi-server queuing system involving a number of servers at every pipe-end that perform their tasks in a synchronized manner. Based on priority rules, the model decides which server should dispatch the entity waiting for service to the associated depot. Each priority rule can lead to a different delivery schedule, which is evaluated by using several criteria. Combined with optimization tools, the proposed simulation technique permits to easily manage real-world pipelines operations with low computational effort.

[1]  Randall P. Sadowski,et al.  Simulation with Arena , 1998 .

[2]  A. Herrán,et al.  A mathematical model for planning transportation of multiple petroleum products in a multi-pipeline system , 2010, Comput. Chem. Eng..

[3]  Álvaro García-Sánchez,et al.  Combining Simulation and Tabu Search for Oil-derivatives Pipeline Scheduling , 2008, Metaheuristics for Scheduling in Industrial and Manufacturing Applications.

[4]  Leandro Magatão,et al.  An efficient approach to the operational scheduling of a real-world pipeline network , 2007 .

[5]  José M. Pinto,et al.  A novel continuous time representation for the scheduling of pipeline systems with pumping yield rate constraints , 2008, Comput. Chem. Eng..

[6]  Flávio Neves,et al.  A mixed integer programming approach for scheduling commodities in a pipeline , 2004, Comput. Chem. Eng..

[7]  Jaime Cerdá,et al.  Optimal Scheduling of Refined Products Pipelines with Multiple Sources , 2009 .

[8]  H. D. Ratliff,et al.  Sequencing inputs to multi-commodity pipelines , 1995, Ann. Oper. Res..

[9]  Jaime Cerdá,et al.  Optimal scheduling of multiproduct pipeline systems using a non-discrete MILP formulation , 2004, Comput. Chem. Eng..

[10]  S. Ramani,et al.  PIPES: A heuristic search model for pipeline schedule generation , 1997, Knowl. Based Syst..

[11]  Ricardo Lüders,et al.  An integrated framework for operational scheduling of a real-world pipeline network , 2008 .

[12]  Jaime Cerdá,et al.  Dynamic scheduling of multiproduct pipelines with multiple delivery due dates , 2008, Comput. Chem. Eng..

[13]  Jeffrey D. Kelly,et al.  Multi-Product Inventory Logistics Modeling in the Process Industries , 2009 .

[14]  Ricardo Lüders,et al.  Simulating the operational scheduling of a realworld pipeline network , 2007 .

[15]  José M. Pinto,et al.  Scheduling of a multiproduct pipeline system , 2003, Comput. Chem. Eng..