A new mixed integer model and iterative solution approach for scheduling and planning of multi product oil pipeline

Document Type : Original Paper


Department of Applied Mathematics, Amir Kabir University of Technology, Tehran, Iran


The problem of pipeline planning is one of the most complex problems in the field of applied and industrial problems. Multi product pipeline planning and inventory management in distribution centers has to consider the pipeline limitations as well as the operational restrictions. Another important issue is the customer demands that must be satisfy on time. Providing effective mathematical models, that cover different aspects of this problem, as well as appropriate solving methods helps to planner to achieve the optimal scheduling of pipelines. Many researchers have been working on models to provide efficient models and develop appropriate methods for solving this problem. In this paper, a new mixed integer optimization model (MILP) is proposed for scheduling and planning multiple product pipelines that connect a refinery to a distribution center. The advantage of this model is its formulation method, which attempts to reduce the number of binary variables used in the model and reduce the complexity of the mathematical model. For this purpose, the problem has first been formulated without taking into account some operational constraints and during the model's solving, by applying an iterative algorithm, these restrictions are added to the model step by step. Finally, to validate models and solving methods, by implementing the proposed models and solution methods on real pipeline systems (based on information from Iran Telecom and Oil Pipelines), the outputs in terms of solving time and quality solution and objective function value are evaluated.


Main Subjects

[1] Techo, R. and Holbrook, D. L. (1974), Computer scheduling the world’s biggest product pipeline, Pipeline Gas Journal, 4, 27.
[2] Hane, C. A. and Ratliff, H. D. (1995), Sequencing inputs to multi-commodity pipelines, Annals of operations research, 57(1), 73-101.
[3] Cafaro, D. C. and Cerda, J. (2004), Optimal scheduling of multiproduct pipeline systems using a nondiscrete MILP formulation, Computers and Chemical Engineering, 28(10), 2053–2068.
[4] Relvas, S., Matos, H. A., Barbosa-Po´voa, A. F. D., Fialho, J. O. and Pinheiro, A. N. S. (2006), Pipeline Scheduling and Inventory Management of a Multiproduct Distribution Oil System, Industrial and Engineering Chemistry Research, 45(23), 7841-7855.
[5] Cafaro, D. C. and Cerda, J. (2008), Efficient Tool for the Scheduling of Multiproduct Pipelines and Terminal Operations, Industrial and Engineering Chemistry Research, 47(24), 9941-9956.
[6] Cafaro, D. C. and Cerda, J. (2009), Optimal Scheduling of Refined Products Pipelines with Multiple Source, Ind. Eng. Chem. Res, 48, 6675–6689.
[7] Cafaro, D. C. and Cerda, J. (2010), Operational scheduling of refined products pipeline networks with simultaneous batch injections, Computers and Chemical Engineering, 34, 1687–1704.
[8] Cafaro, V. G., Cafaro, D. C., Mendez, C. A. M. and Cerda, J. (2012), Detailed Scheduling of Single-Source Pipelines with Simultaneous Deliveries to Multiple Offtake Stations, Industrial & Engineering Chemistry Research, 51, 6145-6165.
[9] Cafaro, G. E. A. (2015), MINLP model for the detailed scheduling of refined products pipelines with flow rate dependent pumping costs, computers and Chemical Engineering, 72, 210-221.
[10] MirHassani, S. A., Moradi, S. and Taghinezhad, N. (2011), Algorithm for long-term scheduling of multi-product pipelines, Industrial & Engineering Chemistry Research, 50, 13899-13910.
[11] MirHassani, S. A. and BeheshtiAsl, N. (2013), A heuristic batch sequencing for multiproduct pipelines, Computers and Chemical Engineering, 56, 58-67.
[12] MirHassani, S. A., Abbasi, M. and Moradi, S. (2013), Operational scheduling of refined product pipeline with dual purpose depots, Applied mathematical modeling, 37, 5723-5742.
[13] Relvas, S., Matos, H. A., Barbosa-Po´voa, A. F. D. and Fialho, J. O. (2013), Integrated scheduling and inventory management of an oil products distribution system, Omega, 41, 955-968.
[14] Kirschstein, T. (2018), Planning of multi-product pipelines by economic lot scheduling models, European Journal of Operational Research, 264, 327–339.
[15] Hitoshi, W., Meira, T., Magatão, L. and Relvas, S. (2018), A matheuristic decomposition approach for the scheduling of a single-source and multiple destinations pipeline system, European Journal of Applied Mathematics, 327, 41-63.
Volume 9, Issue 2
September 2019
Pages 106-125
  • Receive Date: 18 December 2017
  • Revise Date: 18 June 2019
  • Accept Date: 27 June 2019
  • First Publish Date: 23 September 2019