Abstract
This paper addresses the scheduling and inventory management of a straight pipeline system connecting a single refinery to multiple distribution centers. By increasing the number of batches and time periods, maintaining the model resolution by using linear programming-based methods and commercial solvers would be very time-consuming. In this paper, we make an attempt to utilize the problem structure and develop a decomposition-based algorithm capable of finding near-optimal solutions for large instances in a reasonable time. The algorithm starts with a relaxed version of the model and adds a family of cuts on the fly, so that a near-optimal solution is obtained within a few iterations. The idea behind the cut generation is based on the knowledge of the underlying problem structure. Computational experiments on a real-world data case and some randomly generated instances confirm the efficiency of the proposed algorithm in terms of the solution quality and time.
Highlights
Planning the transmission of oil products is a challenging problem in the oil industry
Oil products are produced at the refinery and injected at appropriate pumping rates into the pipeline in the form of batches, and these are discharged at distribution centers (DCs)
We concentrate on the problem of scheduling and inventory management of a straight pipeline system connecting a single refinery to multiple DCs, referred to as the long-term multi-product pipeline scheduling problem (LMPSP)
Summary
Planning the transmission of oil products is a challenging problem in the oil industry. The heuristic method addressed by MirHassani and BeheshtiAsl (2013) is efficient for straight systems connecting a single refinery to a single DC It first determines the sequence of products and effectively manages the inventory level of storage tanks by tracing the location of batches inside the pipeline. Benders’ algorithm (Benders 1962) is a well-known decomposition-based method widely used to efficiently solve different complex problems In this approach, the variables obtained by the MP are fixed to the SP, and the SP is solved for remaining variables. We concentrate on the problem of scheduling and inventory management of a straight pipeline system connecting a single refinery to multiple DCs, referred to as the long-term multi-product pipeline scheduling problem (LMPSP) In this regard, we consider the model proposed by MirHassani et al (2011) as a base.
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