A Post-Pareto Approach for Multi-Objective Decision Making Using a Non-Uniform Weight Generator Method

Carrillo, Victor M.; Taboada, Heidi A.

doi:10.1016/j.procs.2012.09.040

Cited by 18 publications

(6 citation statements)

References 9 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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show abstract

“…There are two general approaches to solving multiple-objective problems (Carrillo & Taboada, 2012). The first approach involves the aggregation of all the objective functions into a single composite objective function.…”

Section: Mathematical Modelling Based Approaches In Gscmmentioning

confidence: 99%

“…The output of this method is a single solution. In contrast, multiple objective evolutionary algorithms offer the decision-maker a set of trade-off solutions usually called non dominated solutions or Pareto-optimal solutions (Carrillo & Taboada, 2012). By definition, a Pareto is a set where none of the objective functions can be improved without worsening the value of another objective function (Caramia & Dell'Olmo, 2008).…”

Section: Mathematical Modelling Based Approaches In Gscmmentioning

confidence: 99%

Multi-objective decision model for green supply chain management

Chanchaichujit

Balasubramanian

Shukla

et al. 2020

Cogent Business & Management

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In this paper, a multi-objective linear programming model was developed which sought to simultaneously optimize total costs and total GHG emissions for the Thai Rubber supply chain. The model was solved by the ε -constraint method which computed the Pareto optimal solution. Each point in the Pareto set entailed a different design of quantity of rubber product flow between the supply chain entities and transport modes and routes. The result obtained show the trade-offs between costs and GHG emissions. It appears that improvements in cost reductions are only possible by compromising on and allowing for higher GHG emissions. From the Pareto set of solutions, each point is equally effective solution for achieving significant cost reductions without compromising too far on GHG emissions. Scenarios analysis were considered to examine the impact of transportation and distribution restructuring on the trade-off between GHG emissions and costs vis-àvis the baseline model. Overall, the model developed in this research, together with its Pareto optimal solutions analysis, shows that it can be used as an effective tool to design a new and workable GSCM model for the Thai Rubber industry. ABOUT THE AUTHORSJanya Chanchaichujit is an Assistant Professor in Logistics Management in the School of Management at Walailak University in Thailand. Dr. Chanchaichujit has over twenty years industrial, project consultancy and academic work experience. Her research interest focuses on incorporating various aspects of operational research applications, and technologies into the design and operation of sustainable supply chain management.

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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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A Post-Pareto Approach for Multi-Objective Decision Making Using a Non-Uniform Weight Generator Method

Cited by 18 publications

References 9 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

Multi-objective decision model for green supply chain management

Revealed Comparative Advantage Method for Solving Multicriteria Decision-making Problems

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