Hamiltonian transition matrices. - Konstantin Avrachenkov; Ali Eshragh; Jerzy A. Filar (VALUETOOLS, 2011)

A hybrid simulation-optimization algorithm for the Hamiltonian cycle problem. - Ali Eshragh; Jerzy A. Filar; Michael Haythorpe (Ann. Oper. Res., 2011)

Hamiltonian Cycles, Random Walks, and Discounted Occupational Measures. - Ali Eshragh; Jerzy A. Filar (Math. Oper. Res., 2011)

On Binomial Observations of Continuous-Time Markovian Population Models. - Nigel G. Bean; Robert Elliott; Ali Eshragh; Joshua V. Ross (J. Appl. Probab., 2015)

On transition matrices of Markov chains corresponding to Hamiltonian cycles. - Konstantin Avrachenkov; Ali Eshragh; Jerzy A. Filar (Ann. Oper. Res., 2016)

Planning of complex supply chains: A performance comparison of three meta-heuristic algorithms. - Behnam Fahimnia; Hoda Davarzani; Ali Eshragh (Comput. Oper. Res., 2018)

Learning to Project in Multi-Objective Binary Linear Programming. - Alvaro Sierra-Altamiranda; Hadi Charkhgard; Iman Dayarian; Ali Eshragh; Sorna Javadi (CoRR, 2019)

Average-reward model-free reinforcement learning: a systematic review and literature mapping. - Vektor Dewanto; George Dunn; Ali Eshragh; Marcus Gallagher; Fred Roosta (CoRR, 2020)

Hamiltonian Cycles and Subsets of Discounted Occupational Measures. - Ali Eshragh; Jerzy A. Filar; Thomas Kalinowski; Sogol Mohammadian (Math. Oper. Res., 2020)

An analytical bound on the fleet size in vehicle routing problems: A dynamic programming approach. - Ali Eshragh; Rasul Esmaeilbeigi; Richard H. Middleton (Oper. Res. Lett., 2020)

Toeplitz Least Squares Problems, Fast Algorithms and Big Data. - Ali Eshragh; Oliver Di Pietro; Michael A. Saunders (CoRR, 2021)

A Hybrid Statistical-Machine Learning Approach for Analysing Online Customer Behavior: An Empirical Study. - Saed Alizami; Kasun Bandara; Ali Eshragh; Foaad Iravani (CoRR, 2022)

LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series Data. - Ali Eshragh; Fred Roosta; Asef Nazari; Michael W. Mahoney (J. Mach. Learn. Res., 2022)

SALSA: Sequential Approximate Leverage-Score Algorithm with Application in Analyzing Big Time Series Data. - Ali Eshragh; Luke Yerbury; Asef Nazari; Fred Roosta; Michael W. Mahoney (CoRR, 2024)

Deep Reinforcement Learning for Picker Routing Problem in Warehousing. - George Dunn; Hadi Charkhgard; Ali Eshragh; Sasan Mahmoudinazlou; Elizabeth Stojanovski (CoRR, 2024)

Optimal Experimental Design for Partially Observable Pure Birth Processes. - Ali Eshragh; Matthew P. Skerritt; Bruno Salvy; Thomas McCallum (CoRR, 2024)

Learning to project in a criterion space search algorithm: an application to multi-objective binary linear programming. - Alvaro Sierra-Altamiranda; Hadi Charkhgard; Iman Dayarian; Ali Eshragh; Sorna Javadi (Optim. Lett., 2024)

Deep reinforcement learning for dynamic order picking in warehouse operations. - Sasan Mahmoudinazlou; Abhay Sobhanan; Hadi Charkhgard; Ali Eshragh; George Dunn (Comput. Oper. Res., 2025)

Solving hard bi-objective knapsack problems using deep reinforcement learning. - Hadi Charkhgard; Hanieh Rastegar Moghaddam; Ali Eshragh; Sasan Mahmoudinazlou; Kimia Keshanian (Discret. Optim., 2025)

Ranking Vectors Clustering: Theory and Applications. - Ali Fattahi; Ali Eshragh; Babak Aslani; Meysam Rabiee (CoRR, 2025)