A class of nonlinear multi-objective mixed integer programming model for oil and gas portfolio and algorithm solution

This paper is concerned with the oil & gas assets portfolio. A multi-objective portfolio model of oil & gas assets is studied from two perspectives—scale and revenue. Considering the nonlinear and integer constraints in the model, a class of oil & gas assets portfolio model of nonlinear...

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Veröffentlicht in:Energy exploration & exploitation Jg. 42; H. 2; S. 712 - 726
1. Verfasser: Yan, Wei
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London, England SAGE Publications 01.03.2024
Sage Publications Ltd
SAGE Publishing
Schlagworte:
Algorithms
Constraint modelling
Genetic algorithms
Integer programming
Mixed integer
Multiple objective analysis
Optimization models
Support vector machines
Oil and gas portfolio
support vector machine
nonlinear multi-objective mixed integer programming
ISSN:0144-5987, 2048-4054
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Zusammenfassung:This paper is concerned with the oil & gas assets portfolio. A multi-objective portfolio model of oil & gas assets is studied from two perspectives—scale and revenue. Considering the nonlinear and integer constraints in the model, a class of oil & gas assets portfolio model of nonlinear multi-objective mixed integer programming is established. The weight of the multi-objective is solved by the support vector machine model. A hybrid genetic algorithm, which uses the position displacement strategy of the particle swarm optimizer as a mutation operation, is applied to the optimization model. Finally, two examples are applied to verify the effectiveness of the model and algorithm.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0144-5987
2048-4054
DOI:10.1177/01445987231182448