The paper titled ‘A multi-objective optimization approach for the selection of overseas oil projects’, was coauthored with Xi-Yu Li fromSchool of Economics and Management, China University of Geosciences, Wuhan 430074, China ;Xin-Ru Lu fromSchool of Economics and Management, China University of Geosciences , Wuhan 430074, China ; Ni Sheng from School of Business, Macau University of Science and Technology, Macao 999078, China ;Wei Zhou fromEnergy Policy Research Group (EPRG), University of Cambridge, Cambridge CB2 1AG, UK ;Hao-Peng Geng from School of Economics and Management, China University of Geosciences,Wuhan 430074, China ;Shiwei Yu from School of Economics and Management, China University of Geosciences.Wuhan 430074, China.

Abstract

Most good quality overseas oil projects, high in investment returns and abundant in resources, are located in politically unstable regions, where competing objectives present great challenges for investors to make informed decisions. Moreover, most of the existing models are single objective and do not adequately incorporate the unique characteristics of overseas oil investment. To bridge these gaps, this study develops a Non-linear Multiobjective Binary Program (NMBP) to optimize the investment portfolios under three competing objectives. Asolution algorithm is developed to solve this multiple objective program by integrating Non-dominated Sorting Genetic Algorithm II (NSGA-II) with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). NSGA-II searches for the pareto set of optimal investment portfolios and TOPSIS determines the best compromise solution based on the investors’ preferences. Finally, China’s oil investment in the Belt and Road Initiative countries is taken as a case study to demonstrate the feasibility and effectiveness of the proposed approach.

Other information

Publication Date:2020

Journal:Computers & Industrial Engineering

DOI:https://doi.org/10.1016/j.cie.2020.106977

The paper can be accessed here