Workflow scheduling aims to optimize task allocation and execution in cloud-fog​ computing environments. Finding an optimal algorithm for workflow scheduling poses a significant challenge due to the complexity and variability of tasks and resources involved. Although meta-heuristic algorithms...

This study proposes a modified Particle Swarm Optimization (PSO) algorithm based on Hummingbird Flight (HBF) patterns to enhance the search quality and population diversity. The HBF has five concepts: (1) Smaller steps toward position updating are more likely than larger ones, (2) Position...

The transmission lines are used for power distribution across large distances. Different parameters affect the power transmission efficiency, and the quality of service. Furthermore, the transmission system parameter estimation is crucial for power flow analysis, electric power system expansion...

Surface Electromyography (sEMG) is a technique for measuring muscle activity by recording electrical signals from the surface of the body. It is widely used in fields such as medical diagnosis, human-computer interaction, and sports injury rehabilitation. The detection of the onset and offset of...

The primary objective in building predictive analytics models is to achieve optimal accuracy with real datasets. The limitations of existing models lie in their storage capacity, which hinders the progress of generating high accuracy. When a model storage capacity is limited, it may struggle to...

This study presents an integrated multi-criteria decision-making (MCDM) and multi-objective optimization model for green supplier evaluation and optimal order allocation under uncertainty. The Fuzzy-Delphi method is used to refine supplier evaluation criteria, determining the weight of criteria,...

This study addresses the challenges associated with optimal power flow (OPF) management in hybrid power systems incorporating diverse energy sources, particularly focusing on the unpredictability of renewable energy sources (RESs). A novel analytics approach is introduced using Multi-Objective...

This paper proposes a Linear Programming-based Bi-Objective time series Forecasting Algorithm that helps forecast sub-annual short univariate time-series data. The proposed algorithm generates forecasts optimized for a pair of accuracy measures instead of just one. The algorithm is based on the...

This study presents a real-world multi-objective facility location analytics model for determining the number and locations of Temporary Emergency Service Centers (TESCs) for a regional natural gas distribution company in Turkey. These centers are set up temporarily after natural disasters...