A5025502211- Risk and Portfolio Optimization
- Facility Location and Emergency Management
- Optimization and Mathematical Programming
- Hybrid Renewable Energy Systems
- Energy and Environment Impacts
- Reliability and Maintenance Optimization
- COVID-19 epidemiological studies
- Management and Optimization Techniques
- Supply Chain and Inventory Management
- Assembly Line Balancing Optimization
- Advanced Manufacturing and Logistics Optimization
- Scheduling and Optimization Algorithms
- Sustainable Supply Chain Management
- Software Reliability and Analysis Research
- Energy Load and Power Forecasting
- Influenza Virus Research Studies
- SARS-CoV-2 and COVID-19 Research
- Vaccine Coverage and Hesitancy
- Risk and Safety Analysis
- Integrated Energy Systems Optimization
- Vehicle Routing Optimization Methods
- Multi-Criteria Decision Making
- Advanced Queuing Theory Analysis
- Electric Vehicles and Infrastructure
- Advanced Optimization Algorithms Research
Dalhousie University
2018-2025
Kharkiv National University of Radio Electronics
2020
University of Waterloo
2013-2016
A new solution methodology of the capacity design problem a PV-Wind-Diesel-Battery Hybrid Power System (HPS) is presented. The formulated as Linear Programming (LP) model with two objectives: minimizing total cost and CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emissions, while capping Expected Unserved Energy (EUE). Total emissions include, in addition to direct from burning fossil fuel, embedded all system components, obtained...
This study introduces an adaptive robust approach for optimally sizing hybrid renewable energy systems (HRESs) comprising solar panels, wind turbines, batteries, and a diesel generator. It integrates vector auto-regressive models (VAR) neural networks (NN) into dynamic uncertainty sets (DUSs) to address temporal auto-correlations cross-correlations among uncertain parameters like demand supply. These DUSs are compared static independent based on time series (TS) from the literature. An exact...
This paper presents a novel solution approach for variant of the job shop scheduling problem with machine unavailability due to both condition-based preventive maintenance and corrective following random breakdowns. We first provide an exact mathematical formulation under simplifying assumptions, namely that number breakdowns each position on is known, degradation rates are fixed, durations deterministic parameters. Moreover, handle more realistic case stochastic degradation, breakdowns,...
We study a multimodal logistics network for multi-echelon supply chain (SC) with multiple products, considering economic and environmental sustainability shipment consolidation (ShC). The SC is modelled as Mixed Integer Linear Program (MILP) then tested on randomly generated but realistic test instances. effects of ShC in design costs are analyzed, showing that decreases the cost, especially when distance between shipper receiver significant. Moreover, machine learning (ML) approaches...