2022 IEEE Congress on Evolutionary Computation (CEC) by El-Abd, Mohammed

“…RL is used to select the best-performing action among three of them in the optimization process to evolve a set of solution based on the population state and reward value. …”
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Morphology for Planar Hexagonal Modular Self-Reconfigurable Robotic Systems by Sadjadi, Hossein

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Effective solutions for the capacitated vehicle routing problem and for the split delivery vehicle routing problem with time windows. (c2013) by Hilal, Nathalie

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Designing Cellular Mobile Networks Using Non{Deterministic Iterative Heuristics by Sait, Sadiq M.

“…Hence, a randomized, heuristic algorithm, such as Simulated Evolution is used in this work to optimize the transmission costs in cellular networks. …”
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Multi-UAV-Enabled Mobile Edge Computing IoT Systems: Joint Association and Resource Allocation Framework by Abu Farha, Yazan Mahmoud

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MoveSchedule by Zouein, Pierette

“…The layout construction algorithm that underlies MoveSchedule uses Constraint Satisfaction to find the set of all positions that meet the constraints on resources' positions and Linear Programming to find the optimal positions that minimize resource transportation and relocation costs. …”
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Scatter search technique for exam timetabling by Mansour, Nashat

“…We evaluate our suggested technique on real-world university data and compare our results with the registrar’s manual timetable in addition to the timetables of other heuristic optimization algorithms. The experimental results show that our adapted scatter search technique generates better timetables than those produced by the registrar, manually, and by other meta-heuristics.…”
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Design and development of an embedded controller for roboticmanipulator by Bakhashwain, J.M.

“…Since the manipulator speed is limited by the mechanical constraints of the robot arm, the system's throughout should be optimized for generation of the required control law based on the data received from the robot's position sensors. …”
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Evacuation of a highly congested urban city by El Khoury, John

“…In this paper, we present a capacity-constrained routing optimization approach to maximize the total evacuees for short notice evacuation planning in case of both natural and/or man-made disasters. …”
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Dynamic Layout Planning Using a Hybrid Incremental Solution Method by Zouein, Pierrette

“…Construction resources, represented as rectangles, are subjected to two-dimensional geometric constraints on relative locations. The objective is to allow site space to all resources so that no spatial conflicts arise, while keeping distance-based adjacency and relocation costs minimal. …”
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Simulated evolution for timing and low power VLSI standard cell placement by Sait, Sadiq M.

“…For this hard multiobjective combinatorial optimization problem, no known exact and efficient algorithms exist that guarantee finding a solution of specific or desirable quality. …”
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Energy-Aware Physical Synthesis of Deep Neural Networks for Edge-AI Applications in Robotics and VLSI Systems by Arulprakash, Enoch

“…Energy-aware physical synthesis is essential for deploying deep neural networks (DNNs) in edge-AI applications for robotics and VLSI systems, where stringent power, area, and latency constraints prevail. Beyond algorithm-and software-level optimizations such as network compression and compiler techniques, the physical effects during VLSI imple-mentation including clock tree synthesis (CTS), routing congestion, IR-drop, cell sizing, and placement significantly influence energy consumption and timing closure. …”
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Shuffled Linear Regression with Erroneous Observations by Saab, Samer S.

“…We propose an optimal recursive algorithm that updates the estimate from the underdetermined function that is based on that permutation-invariant constraint. …”
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User-centric strategies for resource management in heterogeneous wireless networks with QoS considerations by Abbas, Nadine Fawaz

“…Due to the complexity of the problem, we design sub-optimal hierarchical tree-based algorithms for real-time operation taking into account realistic constraints. …”
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Boosting the Training of Neural Networks Through Hybrid Metaheuristics by Abou Doush, Iyad

“…In this paper, six versions of memetic algorithms (MAs) are proposed to replace gradient descent learning mechanism of MLP where adaptive β�-hill climbing (Aβ�HC) as a local search algorithm is hybridized with six population-based metaheuristics which are hybrid flower pollination algorithm, hybrid salp swarm algorithm, hybrid crow search algorithm, hybrid grey wolf optimization (HGWO), hybrid particle swarm optimization, and hybrid JAYA algorithm. …”
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A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…<p>The energy internet (EI) is evolving toward decentralized, data-rich, and time-critical operation, where legacy optimization often fails to meet complexity, scalability, and real-time constraints. …”

A METHODOLOGY FOR NETWORK TOPOLOGY DESIGN USING FUZZY EVALUATIONS by Khan, Salman A.

“…In this paper, we present a methodology to address design issues. This methodology is based on two algorithms, namely, fuzzy simulated evolution algorithm and the augmenting path algorithm. …”
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Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation by Fawaz Kserawi (16904859)

“…We describe our differentially-private model with flexible constraints and a dynamic window algorithm to maintain the privacy-budget loss in infinitely generated time-series data. …”

A linear programming approach for the weighted graph matchingproblem by Almohamad, H.A.

“…A linear program is obtained by formulating the graph matching problem in L1 norm and then transforming the resulting quadratic optimization problem to a linear one. The linear program is solved using a simplex-based algorithm. …”
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Energy-Efficient VoI-Aware UAV-Assisted Data Collection in Wireless Sensor Networks by Kalash, Saeddin

“…In the second, we consider optimized UAV position adaptation where we generated the problem as a multi-objective optimization problem and solved it as a mixed-integer linear programming problem with constraints related to UAV range, UAV steps, and time constraints. …”
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