Optimization model for the detailed scheduling of multi-source pipelines
Vanina G. Cafaro, Diego C. Cafaro, Carlos A. Méndez, Jaime Cerdá
Abstract
Open-access reader
Vanina G. Cafaro, Diego C. Cafaro, Carlos A. Méndez, Jaime Cerdá
Abstract
Open-access reader
Pipeline networks are the shippers’ first choice for carrying large volumes of refined petroleum products from oil refineries to distant distribution terminals. Optimization approaches for solving the pipeline scheduling problem proceed in two hierarchical stages: the aggregate and the detailed planning steps. The aggregate plan determines the batch sizes, the sequence of batch injections, and the allocation of batches to customers. The subsequent stage refines the aggregate plan to find the detailed schedule of batch input and output operations. This paper presents a mixed-integer linear programming (MILP) formulation for the detailed scheduling of multi-source pipelines that accounts for parallel batch injections and simultaneous product deliveries to multiple terminals. It overcomes a critical drawback of previous models that assume single source configurations. Modeling multi-source pipeline networks is a great challenge, requiring a completely revised approach. The new model finds cost-effective solutions with remarkable efficiency.
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Pipeline networks are the shippers’ first choice for carrying large volumes of refined petroleum products from oil refineries to distant distribution terminals. Optimization approaches for solving the pipeline scheduling problem proceed in two hierarchical stages: the aggregate and the detailed planning steps. The aggregate plan determines the batch sizes, the sequence of batch injections, and the allocation of batches to customers. The subsequent stage refines the aggregate plan to find the detailed schedule of batch input and output operations. This paper presents a mixed-integer linear programming (MILP) formulation for the detailed scheduling of multi-source pipelines that accounts for parallel batch injections and simultaneous product deliveries to multiple terminals. It overcomes a critical drawback of previous models that assume single source configurations. Modeling multi-source pipeline networks is a great challenge, requiring a completely revised approach. The new model finds cost-effective solutions with remarkable efficiency.
Key concepts: Scheduling (production processes), Pipeline transport, Oil refinery, Pipeline (software), Mathematical optimization, Computer science, Schedule, Integer programming