19 citations · 28 across the 19 of their papers we have counts for
11 papers · 1 filter
Text2Model: Modeling Copilots for Text-to-Model Translation
Serdar Kadioglu, Karthik Uppuluri, Akash Singirikonda
There is growing interest in leveraging large language models (LLMs) for text-to-model translation and optimization tasks. This paper aims to advance this line of research by intro…
BoolXLLM: LLM-Assisted Explainability for Boolean Models
Du Cheng, Serdar Kadioglu, Xin Wang
Interpretable machine learning aims to provide transparent models whose decision-making processes can be readily understood by humans. Recent advances in rule-based approaches, suc…
Gala: Global LLM Agents for Text-to-Model Translation
Junyang Cai, Serdar Kadioglu, Bistra Dilkina
Natural language descriptions of optimization or satisfaction problems are challenging to translate into correct MiniZinc models, as this process demands both logical reasoning and…
ParBalans: Parallel Multi-Armed Bandits-based Adaptive Large Neighborhood Search
Alican Yilmaz, Junyang Cai, Serdar Kadioglu +1
Solving Mixed-Integer Programming (MIP) problems often requires substantial computational resources due to their combinatorial nature. Parallelization has emerged as a critical str…
Balans: Multi-Armed Bandits-based Adaptive Large Neighborhood Search for Mixed-Integer Programming Problem
Junyang Cai, Serdar Kadioglu, Bistra Dilkina
Mixed-integer programming (MIP) is a powerful paradigm for modeling and solving various important combinatorial optimization problems. Recently, learning-based approaches have show…
Explainable AI using expressive Boolean formulas
Gili Rosenberg, J. Kyle Brubaker, Martin J. A. Schuetz +6
We propose and implement an interpretable machine learning classification model for Explainable AI (XAI) based on expressive Boolean formulas. Potential applications include credit…
Dichotomic Pattern Mining with Applications to Intent Prediction from Semi-Structured Clickstream Datasets
Xin Wang, Serdar Kadioglu
We introduce a pattern mining framework that operates on semi-structured datasets and exploits the dichotomy between outcomes. Our approach takes advantage of constraint reasoning…
Integrated Vehicle Routing and Monte Carlo Scheduling Approach for the Home Service Assignment, Routing, and Scheduling Problem
Shamay G. Samuel, Enrique Areyan Viqueira, Serdar Kadioglu
We formulate and solve the H-SARA Problem, a Vehicle Routing and Appointment Scheduling Problem motivated by home services management. We assume that travel times, service duration…
Column Generation for Interaction Coverage in Combinatorial Software Testing
Serdar Kadioglu
This paper proposes a novel column generation framework for combinatorial software testing. In particular, it combines Mathematical Programming and Constraint Programming in a hybr…
Transformation-based Feature Computation for Algorithm Portfolios
Barry Hurley, Serdar Kadioglu, Yuri Malitsky +1
Instance-specific algorithm configuration and algorithm portfolios have been shown to offer significant improvements over single algorithm approaches in a variety of application do…
DASH: Dynamic Approach for Switching Heuristics
Giovanni Di Liberto, Serdar Kadioglu, Kevin Leo +1
Complete tree search is a highly effective method for tackling MIP problems, and over the years, a plethora of branching heuristics have been introduced to further refine the techn…