Within the oil supply chain, although refinery operations are extensively studied, distribution center operations are not being explored to their full potential. In this paper, these types of operations are studied. A mixedinteger linear programming (MILP) approach is used to model the problem of oil derivatives pipeline transportation scheduling and supply management. The objective of the model is to attain a high level of operation, satisfying clients and accounting for distribution center restrictions and compulsory tasks. First, a base model is developed, which accounts for product transportation, inventory management, and daily client satisfaction. Later, an extension is presented to account for a settling period for each new lot that arrives at the distribution center. A pumping schedule, including the product sequence, lot volume, and timing issues, is obtained. Also, the inventory management is performed while accounting for daily clients requests and quality control tasks. A continuous representation of both time and pipeline volume is used. The model is applied to a real-world case study of a Portuguese oil distribution company, Companhia Logı ´stica de Combustı ´veis (CLC). Different scenarios are outlined, with the objective of analyzing how the settling period and its minimum duration influence the model performance. Various modeling approaches to the product sequence inside the pipeline have been studied. The results are discussed and compared to the real schedule of a typical monthly plan that has been developed by CLC's schedulers.

Pipelines have been proved to be an efficient and economic way to transport oil products. However, the determination of the scheduling of operational activities in pipeline networks is a difficult task, and efficient methods to solve such complex problem are required. In this contribution, a real-world pipeline network is studied, and an optimization model is proposed in order to address the network scheduling activities. A hierarchical approach is proposed on the basis of the integration of a mixed integer linear programming (MILP) model and a set of heuristic modules. This article exploits the MILP model, the main goal of which is to determine the exact time instants that products should be pumped into the pipelines and received in the operational areas. These time instants must satisfy the pipeline network management and operational constraints for a predefined planning period. Such operational constraints include pipeline stoppages, movement of batches through many areas/pipelines, use of preferential routes to avoid contamination losses, on-peak demand hours of pumping, local constraints, reversions of flow direction, and surge tank operations, while satisfying a series of production/consumption requirements. The developed continuous-time model is applied to a large real-world pipeline system, where more than 14 oil derivatives and ethanol are transported and distributed between supply and demand nodes.

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In the oil industry, any improvement in the planning and execution of the associated operations (e.g., production, storage, distribution) can generate considerable profits. To achieve this, the related activities need to be optimized. Within these activities, planning and scheduling occur at the different levels of the oil supply chain, from the strategic to the operational levels looking from global networks to sets of individual resources. This work looks into the planning, namely the assignment/ sequencing of activities that occur in a multiproduct, multipipeline system. The aim is to contribute to the definition of generic models that can help the decision-making process characterized by a high level of complexity. An approach formed by two mixed integer linear programming (MILP) formulations that act in sequence is proposed. The first generic MILP planning model calculates volumes for attending the necessary requirements on inventory management of the producer and consumer areas. As a result, this model defines the products and the total volumes to be transported in order to attain storage goals, while respecting operational constraints, demands of consumers, and pipeline capacity. Then, the planning model results are used by an MILP assignment and sequencing model, which splits the total volume into operational batches and determines the sequence of pumping for the batches during the available horizon. The developed approach is applied to a real-world pipeline network that includes 30 bidirectional multiproduct pipelines associated with 14 node areas: four refineries, two harbors, six depots/parks of pumps and valves, and two final clients.

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