Dr. Botsalı’s current academic interests include;

1. Facilities Planning and Design  

His research in facilities planning and design focuses on data-driven, model-based decisions for configuring production and service systems—covering facility layout, line balancing, capacity planning, and material-handling design. He uses discrete-event simulation and simulation-based optimization to evaluate alternative layouts and control policies under realistic variability, and he formulates multi-objective optimization models (e.g., MILP/CP and metaheuristics such as GA/PSO) to trade off throughput, WIP, travel distance, energy use, and ergonomics. 

2. Mathematical Programming

His research in mathematical programming centers on building exact and hybrid optimization models to support high-stakes planning and operations decisions. He formulates linear, integer, and mixed-integer programs (and when needed MINLP/CP) that capture real-world constraints such as precedence, sequence-dependent setups, duty-time regulations, and resource calendars.

3. Meta-Heuristics

His research in meta-heuristics focuses on designing population- and trajectory-based methods—such as GA, PSO, and hybridizing them with mathematical programming and discrete-event simulation to tackle large, noisy, multi-objective problems.

4. Scheduling

His research in scheduling spans deterministic and stochastic models for single/parallel machines, flow-shop, job-shop, flexible job-shop, and hybrid flow-shop environments, as well as constrained assignments like crew rostering and referee allocation.

5. Data Mining

His research in data mining centers on end-to-end, reproducible pipelines that transform raw scholarly and operational data into actionable insights. He builds robust acquisition and cleaning workflows (web scraping, record linkage, fuzzy deduplication, Unicode/diacritic normalization) and engineers features for heterogeneous sources—structured bibliographic fields, text titles/abstracts/keywords), and graphs of collaboration and citation.