A Comprehensive Review on Single- and Multi-Objective Optimization of Liquid Composite Moulding Process

2021 ◽  
pp. 57-66
Author(s):  
Anita Zade ◽  
Raghu Raja Pandiyan Kuppusamy
Keyword(s):  
Multi Objective Optimization ◽  
Comprehensive Review ◽  
Moulding Process ◽  
Multi Objective ◽  
Liquid Composite Moulding

scholarly journals The Averaged Hausdorff Distances in Multi-Objective Optimization: A Review

Mathematics ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 894 ◽  
Author(s):  
Bogoya ◽  
Vargas ◽  
Schütze
Keyword(s):  
Quality Indicators ◽  
Pareto Optimality ◽  
Optimization Problems ◽  
Multi Objective Optimization ◽  
Finite Sets ◽  
Comprehensive Review ◽  
Multi Objective ◽  
Metric Properties

A brief but comprehensive review of the averaged Hausdorff distances that have recentlybeen introduced as quality indicators in multi-objective optimization problems (MOPs) is presented.First, we introduce all the necessary preliminaries, definitions, and known properties of thesedistances in order to provide a stat-of-the-art overview of their behavior from a theoretical pointof view. The presentation treats separately the definitions of the (p, q)-distances GDp,q, IGDp,q, and Δp,q for finite sets and their generalization for arbitrary measurable sets that covers as an importantexample the case of continuous sets. Among the presented results, we highlight the rigorousconsideration of metric properties of these definitions, including a proof of the triangle inequalityfor distances between disjoint subsets when p, q ≥ 1, and the study of the behavior of associatedindicators with respect to the notion of compliance to Pareto optimality. Illustration of these resultsin particular situations are also provided. Finally, we discuss a collection of examples and numericalresults obtained for the discrete and continuous incarnations of these distances that allow for anevaluation of their usefulness in concrete situations and for some interesting conclusions at the end,justifying their use and further study.

A Comprehensive Review of Machine Learning in Multi-objective Optimization

2021 ◽  
Author(s):  
Qu Qu ◽  
Zheng Ma ◽  
Anders Clausen ◽  
Bo Norregaard Jorgensen
Keyword(s):  
Machine Learning ◽  
Multi Objective Optimization ◽  
Comprehensive Review ◽  
Multi Objective

Synchronous R-NSGA-II: An Extended Preference-Based Evolutionary Algorithm for Multi-Objective Optimization

Informatica ◽  
2015 ◽  
Vol 26 (1) ◽  
pp. 33-50 ◽  
Author(s):  
Ernestas Filatovas ◽  
Olga Kurasova ◽  
Karthik Sindhya
Keyword(s):  
Evolutionary Algorithm ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective

A Heuristic Method Based on Multi-Objective Optimization Concept for Solving RNA Multiple Alignment

2017 ◽  
Vol 10 (5) ◽  
pp. 371
Author(s):  
Arakil Chentoufi ◽  
Abdelhakim El Fatmi ◽  
Molay Ali Bekri ◽  
Said Benhlima ◽  
Mohamed Sabbane
Keyword(s):  
Heuristic Method ◽  
Multiple Alignment ◽  
Multi Objective Optimization ◽  
Multi Objective
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