Title: Evolutionary algorithms for integrated oil and gas supply chain management considering enhanced oil recovery methods

Authors: Raheleh Ardestani; Esmaeil Mehdizadeh; Farhad Etebari

Addresses: Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran ' Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran ' Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran

Abstract: The aim of this study is to model and solve the problem of integrated oil and gas supply chain management (SCM) considering the enhanced oil recovery (EOR) methods in upstream and midstream sectors. For this purpose, the problem is modelled as a bi-objective mixed integer nonlinear program and solved by using BARON solver in the GAMS software. The LP-metric method is used to solve the bi-objective problem. In addition, we used three evolutionary algorithms, namely non-dominated sorting genetic algorithm (NSGAII), multi-objective whale optimisation algorithm (MOWOA), and multi-objective cuckoo search algorithm (MOCSA) to solve the problems of large sizes. To investigate the efficiency of the solution method, 15 problems were solved with a wide range of dimensions. Based on the results, small-size problems can be solved in less than 100 seconds to reach a relative gap of 0.01. However, the solution time increases rapidly when the size of the problem increases. The results of the evolutionary algorithms show that these algorithms (especially MOWOA) can solve the large problems in a reasonable time. In addition, MOWOA is superior to other implemented algorithms in terms of multi-objective solution quality measures. [Received: March 3, 2023; Accepted: October 27, 2023]

Keywords: oil; gas; supply chain management; SCM; enhanced oil recovery; multi-objective; whale optimisation; NSGAII; cuckoo search.

DOI: 10.1504/IJOGCT.2024.142058

International Journal of Oil, Gas and Coal Technology, 2024 Vol.36 No.4, pp.391 - 428

Received: 01 Mar 2023
Accepted: 27 Oct 2023
Published online: 07 Oct 2024 *

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