Applications and performance of the non-numerical ranking preferences method for post-Pareto optimality

Carrillo, Victor M.; Aguirre, Oswaldo; Taboada, Heidi A.

doi:10.1016/j.procs.2011.08.045

Cited by 12 publications

(5 citation statements)

References 7 publications

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“…Had we expanded the selection criteria to include other factors (such as reproduction of reaction pathways), it is likely that different force fields would have been chosen for this study. This subjectivity and associated difficulties in selection of a single solution from a set of Pareto-optimal solutions is well-known, with more formal research being conducted − to cull the most promising candidate solutions. However, the focus of this study is to determine if force fields with the ReaxFF or ReaxFF -lg form can be generated using the MOES procedure that will perform as well as or better than the original parametrization toward this user-specified set of criteria, while not requiring user intervention in crafting optimal parameters but rather allowing evolutionary techniques to self-select optimal force fields.…”

Section: Resultsmentioning

confidence: 99%

Parameterizing Complex Reactive Force Fields Using Multiple Objective Evolutionary Strategies (MOES): Part 2: Transferability of ReaxFF Models to C–H–N–O Energetic Materials

Rice

Larentzos

Byrd

et al. 2015

J. Chem. Theory Comput.

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The Multiple Objective Evolutionary Strategies (MOES) algorithm was used to parametrize force fields having the form of the reactive models ReaxFF (van Duin, A. C. T.; Dasgupta, S.; Lorant, F.; Goddard, W. A. J. Phys. Chem. A 2001, 105, 9396) and ReaxFF-lg (Liu, L.; Liu, Y.; Zybin, S. V.; Sun, H.; Goddard, W. A. J. Phys. Chem. A 2011, 115, 11016) in an attempt to produce equal or superior ambient state crystallographic structural results for cyclotrimethylene trinitramine (RDX). Promising candidates were then subjected to molecular dynamics simulations of five other well-known conventional energetic materials to assess the degree of transferability of the models. Two models generated through the MOES search were shown to have performance better than or as good as ReaxFF-lg in describing the six energetic systems modeled. This study shows that MOES is an effective and efficient method to develop complex force fields.

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Section: Resultsmentioning

confidence: 99%

Parameterizing Complex Reactive Force Fields Using Multiple Objective Evolutionary Strategies (MOES): Part 2: Transferability of ReaxFF Models to C–H–N–O Energetic Materials

Rice

Larentzos

Byrd

et al. 2015

J. Chem. Theory Comput.

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“…Firstly, multiple attributes were sorted non-numerically, and their weights corresponded to w 1 , w 2 , w 3 (w 1 > w 2 > w 3 ). Then, the weights of the three attributes were calculated according to the following formulas derived by Carrillo [41] and substituted into TOPSIS to calculate the comprehensive evaluation value of each solution. Finally, the highest comprehensive evaluation value of each solution was recorded in the process of multiple iterations.…”

Section: Topsis Based On Non-numerical Ranking Preferences Methodsmentioning

confidence: 99%

Optimization of Grouting Material Mixture Ratio Based on Multi-Objective Optimization and Multi-Attribute Decision-Making

et al. 2021

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As a solid waste produced by coal combustion, fly ash will cause serious environmental pollution. However, it can be considered as a sustainable and renewable resource to replace partial cement in grouting materials. Fly ash grouting materials re-cement the broken rock mass and improve the mechanical properties of the original structure. It can reinforce the broken surrounding rock of mine roadway. The utilization of fly ash also reduces environmental pollution. Therefore, this paper establishes a new material mixture ratio optimization model to meet the requirement of material property through combining the methods of experimental design and numerical analysis. Based on the Box–Behnken design with 3 factors and 3 levels, a mathematical model is constructed to fit the nonlinear multiple regression functions between material properties and raw materials ratios. The influence of raw materials is analyzed on material properties (the material’s 7-day uniaxial compressive strength, initial setting time, and slurry viscosity). Then, 80 Pareto solutions are obtained through NASG-II algorithm which takes the regression functions as the objective functions for multi-objective optimization of the grouting material ratio. Finally, the best ratio solution of water-cement ratio—0.71, silica fume content—1.73%, and sodium silicate content—2.61% is obtained through the NNRP-TOPSIS method.

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“…However, a limited amount of literature has been devoted to the post-Pareto analysis stage. Usually, this literature is presented in the context of multi-objective decision-making (MODM) problems, and we point out below (without any details) only a few of them: the compromise programming, goal programming, utility function approaches [21,35,40,42], marginal rate of substitution approach [29], nonnumerical ranking preference method [12], Pareto set clustering method [1,36,37], greedy reduction algorithm [39], restricting weight method [26], local search with achievement scalarizing function [31], hybrid method based on fuzzy logic and evolutionary algorithms [22], nonuniform weight generator method [8], sweeping cones method [9], and so on. For an overview of some post-Pareto analysis methods (in the MODM context), see [11].…”

Section: Introductionmentioning

confidence: 99%

Revealed Comparative Advantage Method for Solving Multicriteria Decision-making Problems

Gogodze

2021

Foundations of Computing and Decision Sciences

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This study proposes and analyzes a new method for the post-Pareto analysis of multicriteria decision-making (MCDM) problems: the revealed comparative advantage (RCA) assessment method. An interesting feature of the suggested method is that it uses the solution to a special eigenvalue problem and can be considered an analog/modification in the MCDM context of well-known ranking methods including the authority-hub method, PageRank method, and so on, which have been successfully applied to such fields as economics, bibliometrics, web search design, and so on. For illustrative purposes, this study discusses a particular MCDM problem to demonstrate the practicality of the method. The theoretical considerations and conducted calculations reveal that the RCA assessment method is self-consistent and easily implementable. Moreover, comparisons with well-known tools of an MCDM analysis shows that the results obtained using this method are appropriate and competitive. An important particularity of the RCA assessment method is that it can be useful for decision-makers in the case in which no decision-making authority is available or when the relative importance of various criteria has not been preliminarily evaluated.

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Applications and performance of the non-numerical ranking preferences method for post-Pareto optimality

Cited by 12 publications

References 7 publications

Parameterizing Complex Reactive Force Fields Using Multiple Objective Evolutionary Strategies (MOES): Part 2: Transferability of ReaxFF Models to C–H–N–O Energetic Materials

Parameterizing Complex Reactive Force Fields Using Multiple Objective Evolutionary Strategies (MOES): Part 2: Transferability of ReaxFF Models to C–H–N–O Energetic Materials

Optimization of Grouting Material Mixture Ratio Based on Multi-Objective Optimization and Multi-Attribute Decision-Making

Revealed Comparative Advantage Method for Solving Multicriteria Decision-making Problems

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