Bacteria Swarm Foraging Optimization for Dynamical Resource Allocation in a Multizone Temperature Experimentation Platform. - Mario A. Muñoz; Jesús A. López; Eduardo Caicedo (Analysis and Design of Intelligent Systems using Soft Computing Techniques, 2007)

An artificial beehive algorithm for continuous optimization. - Mario A. Muñoz; Jesús A. López; Eduardo Caicedo (Int. J. Intell. Syst., 2009)

Simplifying the Bacteria Foraging Optimization Algorithm. - Mario A. Muñoz; Saman K. Halgamuge; Wilfredo Alfonso; Eduardo Caicedo (IEEE Congress on Evolutionary Computation, 2010)

Landscape characterization of numerical optimization problems using biased scattered data. - Mario A. Muñoz; Michael Kirley; Saman K. Halgamuge (IEEE Congress on Evolutionary Computation, 2012)

A Meta-learning Prediction Model of Algorithm Performance for Continuous Optimization Problems. - Mario A. Muñoz; Michael Kirley; Saman K. Halgamuge (PPSN (1), 2012)

Decision support systems for the automatic selection of algorithms for continuous optimization problems. - Mario Andrés Muñoz Acosta (2013)

Effects of function translation and dimensionality reduction on landscape analysis. - Mario A. Muñoz; Kate Smith-Miles (CEC, 2015)

Algorithm selection for black-box continuous optimization problems: A survey on methods and challenges. - Mario A. Muñoz; Yuan Sun 003; Michael Kirley; Saman K. Halgamuge (Inf. Sci., 2015)

Exploratory Landscape Analysis of Continuous Space Optimization Problems Using Information Content. - Mario A. Muñoz; Michael Kirley; Saman K. Halgamuge (IEEE Trans. Evol. Comput., 2015)

ICARUS: Identification of complementary algorithms by uncovered sets. - Mario A. Muñoz; Michael Kirley (CEC, 2016)

Non-parametric model of the space of continuous black-box optimization problems. - Mario A. Muñoz; Kate Smith-Miles (GECCO (Companion), 2017)

Generating custom classification datasets by targeting the instance space. - Mario A. Muñoz; Kate Smith-Miles (GECCO (Companion), 2017)

Performance Analysis of Continuous Black-Box Optimization Algorithms via Footprints in Instance Space. - Mario A. Muñoz; Kate Amanda Smith-Miles (Evol. Comput., 2017)

Instance spaces for machine learning classification. - Mario A. Muñoz; Laura Villanova; Davaatseren Baatar; Kate Smith-Miles (Mach. Learn., 2018)

Instance Space Analysis for Unsupervised Outlier Detection. - Sevvandi Kandanaarachchi; Mario A. Muñoz; Kate Smith-Miles (EDML@SDM, 2019)

Instance Space Analysis of Combinatorial Multi-objective Optimization Problems. - Estefania Yap; Mario A. Muñoz; Kate Smith-Miles; Arnaud Liefooghe (CEC, 2020)

On normalization and algorithm selection for unsupervised outlier detection. - Sevvandi Kandanaarachchi; Mario A. Muñoz; Rob J. Hyndman; Kate Smith-Miles (Data Min. Knowl. Discov., 2020)

Generating New Space-Filling Test Instances for Continuous Black-Box Optimization. - Mario A. Muñoz; Kate Smith-Miles (Evol. Comput., 2020)

Sampling Effects on Algorithm Selection for Continuous Black-Box Optimization. - Mario Andrés Muñoz; Michael Kirley (Algorithms, 2021)

On the diversity and robustness of parameterised multi-objective test suites. - Estefania Yap; Mario Andrés Muñoz; Kate Smith-Miles (Appl. Soft Comput., 2021)

Revisiting where are the hard knapsack problems? via Instance Space Analysis. - Kate Smith-Miles; Jeffrey Christiansen; Mario Andrés Muñoz (Comput. Oper. Res., 2021)

An Instance Space Analysis of Regression Problems. - Mario Andrés Muñoz; Tao Yan; Matheus R. Leal; Kate Smith-Miles; Ana Carolina Lorena; Gisele L. Pappa; Rômulo Madureira Rodrigues (ACM Trans. Knowl. Discov. Data, 2021)

andremun/InstanceSpace: February 2021 Update. - Mario Andrés Muñoz; Kate Smith-Miles (Zenodo, 2021)

Examining algorithm behavior using recurrence quantification and landscape analyses. - Mario Andrés Muñoz (GECCO Companion, 2022)

Benchmarking algorithm portfolio construction methods. - Mario Andrés Muñoz; Hamed Soleimani; Sevvandi Kandanaarachchi (GECCO Companion, 2022)

An Instance Space Analysis of Constrained Multi-Objective Optimization Problems. - Hanan Alsouly; Michael Kirley; Mario Andrés Muñoz (CoRR, 2022)

Bifidelity Surrogate Modelling: Showcasing the Need for New Test Instances. - Nicolau Andrés-Thió; Mario Andrés Muñoz; Kate Smith-Miles (INFORMS J. Comput., 2022)

Analyzing randomness effects on the reliability of exploratory landscape analysis. - Mario Andrés Muñoz; Michael Kirley; Kate Smith-Miles (Nat. Comput., 2022)

Informing Multiobjective Optimization Benchmark Construction Through Instance Space Analysis. - Estefania Yap; Mario Andrés Muñoz; Kate Smith-Miles (IEEE Trans. Evol. Comput., 2022)

Dynamic Landscape Analysis for Constrained Multiobjective Optimization Problems. - Hanan Alsouly; Michael Kirley; Mario Andrés Muñoz (AI (1), 2023)

Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances. - Ana Nikolikj; Saso Dzeroski; Mario Andrés Muñoz; Carola Doerr; Peter Korosec; Tome Eftimov (GECCO, 2023)

Enhanced instance space analysis for the maximum flow problem. - Hossein Alipour; Mario Andrés Muñoz; Kate Smith-Miles (Eur. J. Oper. Res., 2023)

Instance Space Analysis of Search-Based Software Testing. - Neelofar; Kate Smith-Miles; Mario Andrés Muñoz; Aldeida Aleti (IEEE Trans. Software Eng., 2023)

An Instance Space Analysis of Constrained Multiobjective Optimization Problems. - Hanan Alsouly; Michael Kirley; Mario Andrés Muñoz (IEEE Trans. Evol. Comput., 2023)

Instance Space Analysis for Algorithm Testing: Methodology and Software Tools. - Kate Smith-Miles; Mario Andrés Muñoz (ACM Comput. Surv., 2023)

Online Per-Instance Algorithm Selection for Constrained Multi-Objective Optimization Problems. - Hanan Alsouly; Michael Kirley; Mario Andrés Muñoz (GECCO Companion, 2024)

Towards an Improved Understanding of Features for More Interpretable Landscape Analysis. - Marcus Gallagher; Mario A. Muñoz (GECCO Companion, 2024)

Sensitivity Analysis of Surrogate-assisted Bilevel Optimisation. - Behzad Moradi; Michael Kirley; Mario Andrés Muñoz Acosta (GECCO Companion, 2024)

Extending Instance Space Analysis to Algorithm Configuration Spaces. - Anthony Rasulo; Kate Smith-Miles; Mario A. Muñoz; Julia Handl; Manuel López-Ibáñez 001 (GECCO Companion, 2024)

Instance Space Analysis and Item Response Theory for Algorithm Testing. - Kate Smith-Miles; Mario Andrés Muñoz; Sevvandi Kandanaarachchi (GECCO Companion, 2024)

Characterising harmful data sources when constructing multi-fidelity surrogate models. - Nicolau Andrés-Thió; Mario Andrés Muñoz; Kate Smith-Miles (Artif. Intell., 2024)

Optimal selection of benchmarking datasets for unbiased machine learning algorithm evaluation. - João Luiz Junho Pereira; Kate Smith-Miles; Mario Andrés Muñoz; Ana Carolina Lorena (Data Min. Knowl. Discov., 2024)

On the impact of initialisation strategies on Maximum Flow algorithm performance. - Hossein Alipour; Mario Andrés Muñoz; Kate Smith-Miles (Comput. Oper. Res., 2024)

Tracing the Interactions of Modular CMA-ES Configurations Across Problem Landscapes. - Ana Nikolikj; Mario Andrés Muñoz; Eva Tuba; Tome Eftimov (CEC, 2025)

Why We Should be Benchmarking Evolutionary Algorithms on Neural Network Training Tasks. - Katherine Mary Malan; Mario Andrés Muñoz (GECCO, 2025)

Instance Space Analysis of the Capacitated Vehicle Routing Problem with Mixture Discriminant Analysis. - Danielle Notice; Hamed Soleimani; Nicos G. Pavlidis; Ahmed Kheiri; Mario Andrés Muñoz (GECCO, 2025)

An Item Response Theory-based R module for Algorithm Portfolio Analysis. - Brodie Oldfield; Sevvandi Kandanaarachchi; Ziqi Xu 001; Mario Andrés Muñoz (SoftwareX, 2025)

Benchmarking footprints of continuous black-box optimization algorithms: Explainable insights into algorithm success and failure. - Ana Nikolikj; Mario Andrés Muñoz; Tome Eftimov (Swarm Evol. Comput., 2025)

instancespace: a Python Package for Insightful Algorithm Testing through Instance Space Analysis. - Yusuf Berdan Güzel; Kushagra Khare; Nathan Harvey; Kian Dsouza; Dong Hyeog Jang; Junheng Chen; Cheng Ze Lam; Mario Andrés Muñoz (CoRR, 2025)