Squirrel Search Algorithm for Portfolio Optimization by Dhaini, Mahdi

“…However, the successes of nature-inspired algorithms in hard computational optimization problems have encouraged researchers to design and apply these algorithms for a variety of optimization problems. …”
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Drones Tracking Adaptation Using Reinforcement Learning: Proximal Policy optimization by Alhadhrami, Esra Ebrahim

“…The Q value plays a crucial role in estimating future state values within a Kalman filter tracking system. Proximal Policy Optimization (PPO), a state-of-the-art policy optimization algorithm, was employed to determine the optimal Q value that enhances tracking performance, as measured by Root Mean Square Error (RMSE). …”
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Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization by De Rochechouart, Maxence

“…In particular, the Proximity Policy Optimization (PPO) reinforcement algorithm is used to discover a policy for sensor selection that results in optimum sensor resource allocation. …”
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Developing a resilient framework for electric vehicle charging stations harnessing solar energy, standby batteries and grid integration with advanced control mechanisms by Debabrata Mazumdar (18560506)

“…Consequently, this article presents and evaluates a system that utilizes a proportional‐integral‐derivative controller, a neural network‐equipped grid and a charging station utilizing a Dragon Fly Optimization Algorithm to generate power and a maximum power point tracking controller. …”

Integrated economic and environmental models for a multi stage cold supply chain under carbon tax regulation by Hariga, Moncer

“…The structural properties for the optimal solution of the three models are identified and solution algorithms are also proposed. …”
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Blood Glucose Regulation Modelling and Intelligent Control by Nasar, Nabeel

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Distributed DRL-Based Downlink Power Allocation for Hybrid RF/VLC Networks by Bekir Sait Ciftler (17541801)

“…Then, we propose a distributed DRL-based algorithm Deep Deterministic Policy Gradient (DDPG), to solve the formulated computationally-intensive problem. …”

Economic Production Lot-Sizing For An Unreliable Machine Under Imperfect Age-Based Maintenance Policy by El-Ferik, S

“…Some useful properties of the cost function are developed to characterize the optimal policy. An algorithm is also proposed to find the optimal solutions to the problem at hand. …”
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Adaptive PPO With Multi-Armed Bandit Clipping and Meta-Control for Robust Power Grid Operation Under Adversarial Attacks by Mohamed Massaoudi (16888710)

“…This paper proposes a novel composite enhanced proximal policy optimization (CePPO) algorithm to improve power grid operation under adversarial conditions. …”

A hybrid model for the optimum integration of renewable technologies in power generation systems by Poullikkas, Andreas

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Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling by Majed Hadid (17148364)

“…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …”

A Novel Genetic Trajectory Planning Algorithm With Variable Population Size for Multi-UAV-Assisted Mobile Edge Computing System by Muhammad Asim (2235472)

“…We aim to minimize the sum of hovering and flying energies of UAVs by optimizing the trajectories of UAVs. …”

Reinforcement Learning for Resilient Aerial-IRS Assisted Wireless Communications Networks in the Presence of Multiple Jammers by Zain Ul Abideen Tariq (17984107)

“…Hence, we leverage the light-weight Deep Reinforcement Learning (DRL) technique called Deep Deterministic Policy Gradient (DDPG) to optimize trajectory and IRS phase shifts and achieve multiple objectives jointly. …”

Multi-Objective Optimization for Food Availability under Economic and Environmental Risk Constraints by Bashar Hassna (19170940)

“…Deploying the Analytical Hierarchy Process (AHP), this study evaluates climate change risks associated with seven different suppliers for three key crops, considering a range of factors, including surface temperature, arable land, water stress, and adaptation policies. Utilizing these assessments, a multi-objective optimization model is developed and solved using MATLAB (R2018a)’s Genetic Algorithm, aiming to identify optimal suppliers to meet Qatar’s food demand, with consideration of the economic, environmental, and risk factors. …”

Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review by Mohamed Sadok Massaoudi (17984071)

“…The ubiquitous DRL architecture, by learning from the dynamism inherent in PSs, produces near-optimal actions for PSS. This article provides a rigorous review of the latest research efforts focused on DRL to derive PSS policies while accounting for the unique properties of power grids. …”

Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle by Reza Jafari (3494018)

“…To this end, three model-free DRL-based methods, based on deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and TD3 enhanced with curriculum learning (CL TD3), are developed for determining optimal yaw moment control and energy optimization online. …”

Experimental Investigation and Comparative Evaluation of Standard Level Shifted Multi-Carrier Modulation Schemes With a Constraint GA Based SHE Techniques for a Seven-Level PUC Inv... by Atif Iqbal (5504636)

“…Different standard multicarrier sinusoidal pulse-width modulation techniques (SPWMs) are adapted for the generation of switching gate signals for the PUC power switches, and these SPWMs are compared with novel optimization-based selective harmonic elimination (SHE) that employs genetic algorithm (GA) for solving nonlinear SHE equation with a constraint that eliminated all third-order harmonics efficiently. …”

Adaptive temperature control of a reverse flow process by using reinforcement learning approach by A. Binid (22046054)

“…First, a policy iteration algorithm is introduced to learn the optimal solution of the associated linear-quadratic control problem online. …”

DRL-Based IRS-Assisted Secure Visible Light Communications by Danya A. Saifaldeen (19498705)

“…The DDPG-based algorithm provides an optimized solution that can adapt to the large size of design parameters and act fast to the channel variations due to users’ mobility. …”

The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions by Abdulmalik Alwarafy (17984104)