Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization by Abu Zitar, Raed

“…Nevertheless, the GOA is unsuitable for addressing multimodal, hybrid functions, and data mining problems. …”
Get full text

A new genetic algorithm approach for unit commitment by Mantawy, A.H.

“…A fitness function is constructed from the total operating cost of the generating units without penalty terms. …”
Get full text
Get full text

Evolutionary algorithms for VLSI multi-objective netlist partitioning by Sait, Sadiq M.

“…Fuzzy rules are incorporated in order to handle the multi-objective cost function. For SimE, fuzzy goodness functions are designed for delay and power, and proved efficient. …”
Get full text

An Evolutionary Algorithm for the Allocation Problem in High-Level Synthesis by Harmanani, Haidar

“…The method performs allocation of functional units, registers, and multiplexers in addition to controller synthesis with the objective of minimizing the cost of hardware resources. …”
Get full text
Get full text
Get full text

A New Penalty Function Algorithm For Convex Quadratic Programming by Bendaya, M.

“…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
Get full text

Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach by Sarif, Bambang

“…The algorithm is tested using 200 randomly generated 2-variable 4-valued functions. …”
Get full text
Get full text

Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

Get full text
Get full text

Simulated evolution algorithm for multiobjective VLSI netlist bi-partitioning by Sait, Sadiq M.

“…The multi-objective version of the problem is addressed in which, power dissipation, timing performance, as well as cut-set are optimized while Balance is taken as a constraint. Fuzzy rules are used in order to design the overall multi-objective cost function that integrates the costs of three objectives in a single overall cost value. …”
Get full text
Get full text

A genetic-based algorithm for fuzzy unit commitment model by Mantawy, A.H.

“…The model takes the uncertainties in the forecasted load demand and the spinning reserve constraints in a fuzzy frame. The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. …”
Get full text
Get full text

STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization by Muhammad Salman Khan (7202543)

Optimization and control of solar-wind islanded hybrid microgrid by using heuristic and deterministic optimization algorithms and fuzzy logic controller by Sk. A., Shezan

Get full text
Get full text
Get full text

Evolutionary algorithms, simulated annealing and tabu search: a comparative study by Youssef, H.

“…This is a hard multi-criteria optimization problem. Fuzzy logic is used to combine all objective criteria into a single fuzzy evaluation (cost) function, which is then used to rate competing solutions. # 2001 Elsevier Science Ltd. …”
Get full text

Improved scatter search algorithm for predicting all-atoms protein structures using charmm22 energy model. (c2010) by Ghalayini, Iman Adnan

Get full text
Get full text

Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem by Mantawy, A.H.

“…The core of the proposed algorithm is based on genetic algorithms. Tabu search is used to generate new population members in the reproduction phase of the genetic algorithm. …”
Get full text
Get full text

Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images by Abu Zitar, Raed

“…The picture histogram is used to display the algorithm's potential solutions. …”
Get full text

A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995) by Moujabber, Bassam N.

Get full text
Get full text

Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

“…The goal is to select a set of sensors based on norms of weighted distances cost function. The norms are the Euclidean distance and the Mahalanobis distance between the drone location and the sensors. …”
Get full text

Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems by Abualigah, Laith

“…In this paper, a novel hybrid optimization algorithm is proposed to solve various benchmark functions, which is called IPDOA. …”
Get full text

A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem by Mantawy, A. H.

“…This paper presents a new algorithm based on integrating the use of genetic algorithms and tabu search methods to solve the unit commitment problem. …”
Get full text

Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem by Montawy, A.H.

“…The core of the proposed algorithm is based on genetic algorithms. Tabu search is used to generate new population members in the reproduction phase of the genetic algorithm. …”
Get full text