Recent contributions to the optimal design of pipeline networks in the energy industry using mathematical programming

Diego C. Cafaro (), Demian J. Presser and Ignacio E. Grossmann
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Diego C. Cafaro: INTEC(UNL-CONICET)
Demian J. Presser: INTEC(UNL-CONICET)
Ignacio E. Grossmann: Carnegie Mellon University

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2022, vol. 30, issue 3, No 8, 618-648

Abstract: Abstract The optimal design of pipeline networks has inspired process systems engineers and operations research practitioners since the earliest times of mathematical programming. The nonlinear equations governing pressure drops, energy consumption and capital investments have motivated nonlinear programming (NLP) approaches and solution techniques, as well as mixed-integer nonlinear programming (MINLP) formulations and decomposition strategies. In this overview paper, we present a systematic description of the mathematical models proposed in recent years for the optimal design of pipeline networks in the energy industry. We provide a general framework to address these problems based on both the topology of the network to build, and the physical properties of the fluids to transport. We illustrate the computational challenges through several examples from industry collaboration projects, published in recent papers from our research group.

Keywords: Pipeline; Network; Energy; Supply chain; Design; Optimization; MINLP; 90B06 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11750-022-00635-3

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