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20222026
most citedDomain-Independent Dynamic Programming: Generic State Space Search for Combinatorial Optimization

6 citations · 6 across the 7 of their papers we have counts for

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7 papers

cs.AI2026

Domain-Independent Dynamic Programming with Constraint Propagation

Imko Marijnissen, J. Christopher Beck, Emir Demirović +1

There are two prevalent model-based paradigms for combinatorial problems: 1) state-based representations, such as heuristic search, dynamic programming (DP), and decision diagrams,…

math.OC2025

Column Generation with Domain-Independent Dynamic Programming

Ryo Kuroiwa, Edward Lam

Column generation and branch-and-price (B&P) are leading mathematical optimization methods for large-scale exact optimization, iterating between solving a master problem and a pric…

cs.AI2025

Reinforcement Learning-based Heuristics to Guide Domain-Independent Dynamic Programming

Minori Narita, Ryo Kuroiwa, J. Christopher Beck

Domain-Independent Dynamic Programming (DIDP) is a state-space search paradigm based on dynamic programming for combinatorial optimization. In its current implementation, DIDP guid…

math.OC2024

Optimization Models for the Quadratic Traveling Salesperson Problem

Yuxiao Chen, Nivetha Sathish, Anubhav Singh +2

The quadratic traveling salesperson problem (QTSP) is a generalization of the traveling salesperson problem, in which all triples of consecutive customers in a tour determine the t…

cs.AI2024

Domain-Independent Dynamic Programming

Ryo Kuroiwa, J. Christopher Beck

For combinatorial optimization problems, model-based paradigms such as mixed-integer programming (MIP) and constraint programming (CP) aim to decouple modeling and solving a proble…

cs.AI2023

Learning Search-Space Specific Heuristics Using Neural Networks

Yu Liu, Ryo Kuroiwa, Alex Fukunaga

We propose and evaluate a system which learns a neuralnetwork heuristic function for forward search-based, satisficing classical planning. Our system learns distance-to-goal estima…

cs.AI2022★ 6 cited

Domain-Independent Dynamic Programming: Generic State Space Search for Combinatorial Optimization

Ryo Kuroiwa, J. Christopher Beck

For combinatorial optimization problems, model-based approaches such as mixed-integer programming (MIP) and constraint programming (CP) aim to decouple modeling and solving a probl…