default search action
10th EMO 2019: East Lansing, MI, USA
- Kalyanmoy Deb, Erik D. Goodman, Carlos A. Coello Coello, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim, Patrick M. Reed:
Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings. Lecture Notes in Computer Science 11411, Springer 2019, ISBN 978-3-030-12597-4
Theory
- Cheikh Toure, Anne Auger, Dimo Brockhoff, Nikolaus Hansen
:
On Bi-objective Convex-Quadratic Problems. 3-14 - Miqing Li
An Empirical Investigation of the Optimality and Monotonicity Properties of Multiobjective Archiving Methods. 15-26 - Mohamed Abouhawwash
Evolutionary Multi-objective Optimization Using Benson's Karush-Kuhn-Tucker Proximity Measure. 27-38 - Ricardo H. C. Takahashi:
On the Convergence of Decomposition Algorithms in Many-Objective Problems. 39-50
Algorithms
- Oliver Cuate, Lourdes Uribe
A New Hybrid Metaheuristic for Equality Constrained Bi-objective Optimization Problems. 53-65 - Maxim Buzdalov:
Make Evolutionary Multiobjective Algorithms Scale Better with Advanced Data Structures: Van Emde Boas Tree for Non-dominated Sorting. 66-77 - Lourdes Uribe
Toward a New Family of Hybrid Evolutionary Algorithms. 78-90 - Hui Li, Jianyong Sun, Qingfu Zhang, Yuxiang Shui:
Adjustment of Weight Vectors of Penalty-Based Boundary Intersection Method in MOEA/D. 91-100 - Azam Asilian Bidgoli
GDE4: The Generalized Differential Evolution with Ordered Mutation. 101-113 - Jialong Shi, Jianyong Sun, Qingfu Zhang:
Multi-objective Techniques for Single-Objective Local Search: A Case Study on Traveling Salesman Problem. 114-125 - Christian Grimme, Pascal Kerschke
Multimodality in Multi-objective Optimization - More Boon than Bane? 126-138 - Jing-Yu Ji
Solving Nonlinear Equation Systems Using Multiobjective Differential Evolution. 139-150 - Carlos A. Escobar, Diana M. Wegner, Abhinav Gaur, Rubén Morales-Menéndez:
Process-Monitoring-for-Quality - A Model Selection Criterion for Genetic Programming. 151-164 - Mengjun Ming, Rui Wang
Evolutionary Many-Constraint Optimization: An Exploratory Analysis. 165-176
Many-Objective EMO
- Kalyanmoy Deb
Generating Uniformly Distributed Points on a Unit Simplex for Evolutionary Many-Objective Optimization. 179-190 - Dhish Kumar Saxena, Sarang Kapoor
On Timing the Nadir-Point Estimation and/or Termination of Reference-Based Multi- and Many-objective Evolutionary Algorithms. 191-202 - Oliver Cuate, Oliver Schütze:
Variation Rate: An Alternative to Maintain Diversity in Decision Space for Multi-objective Evolutionary Algorithms. 203-215 - Auraham Camacho, Gregorio Toscano Pulido, Ricardo Landa Becerra, Hisao Ishibuchi:
Indicator-Based Weight Adaptation for Solving Many-Objective Optimization Problems. 216-228 - Julian Blank
Investigating the Normalization Procedure of NSGA-III. 229-240 - Hojjat Rakhshani, Lhassane Idoumghar, Julien Lepagnot, Mathieu Brévilliers:
MAC: Many-objective Automatic Algorithm Configuration. 241-253 - Alberto Rodríguez Sánchez, Antonin Ponsich, Antonio López Jaimes, Saúl Zapotecas Martínez
A Parallel Tabu Search Heuristic to Approximate Uniform Designs for Reference Set Based MOEAs. 254-265 - Dani Irawan
Comparison of Reference- and Hypervolume-Based MOEA on Solving Many-Objective Optimization Problems. 266-277 - Deepak Sharma
Diversity over Dominance Approach for Many-Objective Optimization on Reference-Points-Based Framework. 278-290 - Yi Wu, Bin Li, Sanchao Ding, Yinda Zhou:
A Two-Stage Evolutionary Algorithm for Many-Objective Optimization. 291-304
Performance Metrics and Indicators
- Jesús Guillermo Falcón-Cardona
CRI-EMOA: A Pareto-Front Shape Invariant Evolutionary Multi-objective Algorithm. 307-318 - Sabrina M. Oliveira, Elizabeth F. Wanner
The Hypervolume Indicator as a Performance Measure in Dynamic Optimization. 319-331 - Hisao Ishibuchi, Ryo Imada, Naoki Masuyama, Yusuke Nojima
Comparison of Hypervolume, IGD and IGD+ from the Viewpoint of Optimal Distributions of Solutions. 332-345 - Yali Wang, Michael Emmerich
Diversity-Indicator Based Multi-Objective Evolutionary Algorithm: DI-MOEA. 346-358 - André H. Deutz, Michael Emmerich
The Expected R2-Indicator Improvement for Multi-objective Bayesian Optimization. 359-370
Innovization and Surrogates
- Proteek Chandan Roy
Trust-Region Based Multi-objective Optimization for Low Budget Scenarios. 373-385 - Yuri Marca, Hernán E. Aguirre, Saúl Zapotecas Martínez
Approximating Pareto Set Topology by Cubic Interpolation on Bi-objective Problems. 386-398 - Heiner Zille
Linear Search Mechanism for Multi- and Many-Objective Optimisation. 399-410 - Taishi Ito, Hernán E. Aguirre, Kiyoshi Tanaka, Arnaud Liefooghe
Estimating Relevance of Variables for Effective Recombination. 411-423 - João A. Duro
sParEGO - A Hybrid Optimization Algorithm for Expensive Uncertain Multi-objective Optimization Problems. 424-438 - Julian Schulte, Niclas Feldkamp, Sören Bergmann
Knowledge Discovery in Scheduling Systems Using Evolutionary Bilevel Optimization and Visual Analytics. 439-450 - Aimin Zhou
Pareto Optimal Set Approximation by Models: A Linear Case. 451-462 - Atanu Mazumdar
On Dealing with Uncertainties from Kriging Models in Offline Data-Driven Evolutionary Multiobjective Optimization. 463-474 - Bai Yan
Convergence Acceleration for Multiobjective Sparse Reconstruction via Knowledge Transfer. 475-487
Combinatorial EMO
- Keiki Takadama, Keiji Sato, Hiroyuki Sato:
Evolving Generalized Solutions for Robust Multi-objective Optimization: Transportation Analysis in Disaster. 491-503 - Wanru Gao, Mojgan Pourhassan, Vahid Roostapour, Frank Neumann
Runtime Analysis of Evolutionary Multi-objective Algorithms Optimising the Degree and Diameter of Spanning Trees. 504-515 - Jakob Bossek, Christian Grimme, Stephan Meisel, Günter Rudolph, Heike Trautmann:
Bi-objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm. 516-528 - Joseph Billingsley, Ke Li
A Formal Model for Multi-objective Optimisation of Network Function Virtualisation Placement. 529-540 - Behrooz Ghasemishabankareh, Melih Ozlen
NSGA-II for Solving Multiobjective Integer Minimum Cost Flow Problem with Probabilistic Tree-Based Representation. 541-552 - Azam Asilian Bidgoli
Opposition-Based Multi-objective Binary Differential Evolution for Multi-label Feature Selection. 553-564 - Camille Pageau, Aymeric Blot
Configuration of a Dynamic MOLS Algorithm for Bi-objective Flowshop Scheduling. 565-577
MCDM and Interactive EMO
- Marius Bommert
Reliable Biobjective Solution of Stochastic Problems Using Metamodels. 581-592 - Erella Matalon Eisenstadt, Amiram Moshaiov:
Mutual Rationalizability in Vector-Payoff Games. 593-604 - Sunith Bandaru, Amos H. C. Ng:
Trend Mining: A Visualization Technique to Discover Variable Trends in the Objective Space. 605-617 - Rubén Saborido
IRA-EMO: Interactive Method Using Reservation and Aspiration Levels for Evolutionary Multiobjective Optimization. 618-630 - Ke Li
Progressive Preference Learning: Proof-of-Principle Results in MOEA/D. 631-643 - Erica Berghman, Yves De Smet, Jean Rosenfeld, Dimitri Van Assche:
A Dichotomous Approach to Reduce Rank Reversal Occurrences in PROMETHEE II Rankings. 644-654 - Carolina Gil Marcelino
A Viability Study of Renewables and Energy Storage Systems Using Multicriteria Decision Making and an Evolutionary Approach. 655-668
Applications
- Koen van der Blom
Analysing Optimisation Data for Multicriteria Building Spatial Design. 671-682 - Courtney Powell, Katsunori Miura, Masaharu Munetomo:
Constrained Multi-objective Optimization Method for Practical Scientific Workflow Resource Selection. 683-694 - Proteek Chandan Roy
Simulation Optimization of Water Usage and Crop Yield Using Precision Irrigation. 695-706 - Kalyan Shankar Bhattacharjee, Hemant Kumar Singh
Optimum Wind Farm Layouts: A Many-Objective Perspective and Case Study. 707-718 - William R. Jensen, Thang Q. Pham, Shanelle N. Foster:
Comparison of Multi-objective Optimization Methods Applied to Electrical Machine Design. 719-730 - Fateme Azimlu
Designing Solar Chimney Power Plant Using Meta-modeling, Multi-objective Optimization, and Innovization. 731-742 - Renê Pinto, Hugo Silva
Neuroevolutionary Multiobjective Methodology for the Optimization of the Injection Blow Molding Process. 743-754
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2025-01-02 18:23 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: