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

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.