SO-MODS: Optimization for high dimensional computationally expensive multi-modal functions with surrogate search. - Juliane Müller 004; Tipaluck Krityakierne; Christine A. Shoemaker (IEEE Congress on Evolutionary Computation, 2014)

Global Optimization with Sparse and Local Gaussian Process Models. - Tipaluck Krityakierne; David Ginsbourger (MOD, 2015)

SOP: parallel surrogate global optimization with Pareto center selection for computationally expensive single objective problems. - Tipaluck Krityakierne; Taimoor Akhtar; Christine A. Shoemaker (J. Glob. Optim., 2016)

Comment: Some Enhancements Over the Augmented Lagrangian Approach. - Victor Picheny; David Ginsbourger; Tipaluck Krityakierne (Technometrics, 2016)

SOMS: SurrOgate MultiStart algorithm for use with nonlinear programming for global optimization. - Tipaluck Krityakierne; Christine A. Shoemaker (Int. Trans. Oper. Res., 2017)

Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization. - Poompol Buathong; David Ginsbourger; Tipaluck Krityakierne (AISTATS, 2020)

A Comparative Study of Infill Sampling Criteria for Computationally Expensive Constrained Optimization Problems. - Kittisak Chaiyotha; Tipaluck Krityakierne (Symmetry, 2020)

Optimization Models for Efficient (t, r) Broadcast Domination in Graphs. - Poompol Buathong; Tipaluck Krityakierne (Symmetry, 2021)

The card guessing game: A generating function approach. - Tipaluck Krityakierne; Thotsaporn "Aek" Thanatipanonda (J. Symb. Comput., 2023)

Market Analysis with Business Intelligence System for Marketing Planning. - Treerak Kongthanasuwan; Nakarin Sriwiboon; Banpot Horbanluekit; Wasakorn Laesanklang; Tipaluck Krityakierne (Inf., 2023)

GDESA: Gradient Differential Evolution-Simulated Annealing Hybrid. - Bhumrapee Soonjun; Tipaluck Krityakierne (IEEE Access, 2024)

von Neumann and Newman Pokers with Finite Decks. - Tipaluck Krityakierne; Thotsaporn Thanatipanonda; Doron Zeilberger (CoRR, 2024)

Embedded Vehicle Routing Problem: A Modeling and Optimization Framework for Real-World Multi-Purpose Truck Network. - Tipaluck Krityakierne; Chanon Boonkangwan; Chanoknun Phunnasorn; Wasakorn Laesanklang (IEEE Access, 2025)

Caged Markov process - A continuous-time framework for modeling a constrained Markov process within a freely-evolving Markov process. - Tanes Printechapat; Pakorn Aiewsakun; Tipaluck Krityakierne (Math. Comput. Simul., 2025)