Online multi-criteria portfolio analysis through compromise programming models built on the underlying principles of fuzzy outranking

Rivera, Gilberto; Florencia, Rogelio; Guerrero, Mario; Porras, Raúl; Sánchez-Solís, J. Patricia

doi:10.1016/j.ins.2021.08.087

Cited by 17 publications

(2 citation statements)

References 42 publications

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“…Fortunately, the preferences of many DMs are non-compensatory. The scientific literature provides recent studies with several satisfactory applications of outranking to real-world problems (e.g., Calafat-Marzal et al, 2021;Doumpos & Figueira, 2019;Liang et al, 2022;Pereira et al, 2019;Rivera et al 2021;Spiliotis et al 2020).…”

Section: Our Proposal: the Aco-based Hyper-heuristicmentioning

confidence: 99%

An ACO-based Hyper-heuristic for Sequencing Many-objective Evolutionary Algorithms that Consider Different Ways to Incorporate the DM's Preferences

Rivera

Cruz-Reyes²,

Fernández³

et al. 2023

Swarm and Evolutionary Computation

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Section: Our Proposal: the Aco-based Hyper-heuristicmentioning

confidence: 99%

An ACO-based Hyper-heuristic for Sequencing Many-objective Evolutionary Algorithms that Consider Different Ways to Incorporate the DM's Preferences

Rivera

Cruz-Reyes²,

Fernández³

et al. 2023

Swarm and Evolutionary Computation

Self Cite

View full text Add to dashboard Cite

“…In this field, Multi-objective Evolutionary Algorithms (MOEAs) are widely recognized. Mainly, the algorithm NSGAII (Non-Dominated Sorting-based multi-objective EA) proposed by [ 30 , 31 ] has been quite effective when handling two or three objectives [ 32 , 33 ]. Based on the survey in [ 34 ], the only related work that uses NSGAII for FBA optimization is by Costanza et al [ 35 ].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Microalgae Metabolism: An Evolutive Algorithm Based on FBA

et al. 2022

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Studies enabled by metabolic models of different species of microalgae have become significant since they allow us to understand changes in their metabolism and physiological stages. The most used method to study cell metabolism is FBA, which commonly focuses on optimizing a single objective function. However, recent studies have brought attention to the exploration of simultaneous optimization of multiple objectives. Such strategies have found application in optimizing biomass and several other bioproducts of interest; they usually use approaches such as multi-level models or enumerations schemes. This work proposes an alternative in silico multiobjective model based on an evolutionary algorithm that offers a broader approximation of the Pareto frontier, allowing a better angle for decision making in metabolic engineering. The proposed strategy is validated on a reduced metabolic network of the microalgae Chlamydomonas reinhardtii while optimizing for the production of protein, carbohydrates, and CO2 uptake. The results from the conducted experimental design show a favorable difference in the number of solutions achieved compared to a classic tool solving FBA.

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Adapting Swarm Intelligence to a Fixed Wing Unmanned Combat Aerial Vehicle Platform

Bakirci,

Ozer

2023

Studies in Big Data

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Online multi-criteria portfolio analysis through compromise programming models built on the underlying principles of fuzzy outranking

Cited by 17 publications

References 42 publications

An ACO-based Hyper-heuristic for Sequencing Many-objective Evolutionary Algorithms that Consider Different Ways to Incorporate the DM's Preferences

An ACO-based Hyper-heuristic for Sequencing Many-objective Evolutionary Algorithms that Consider Different Ways to Incorporate the DM's Preferences

Multi-Objective Optimization of Microalgae Metabolism: An Evolutive Algorithm Based on FBA

Adapting Swarm Intelligence to a Fixed Wing Unmanned Combat Aerial Vehicle Platform

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