[PDF] Top 20 Throughput Optimization in Cooperative Communications using Evolutionary Algorithms

... under cooperative scenarios using various hard combination fusion schemes ...[3]. Optimization performance of cooperative sensing in terms of number of cooperative users is performed ... See full document

... Distributed evolutionary algorithms (dEAs) [22, 23] allocate the tedious computational burden across nu- merous computational nodes, greatly reducing the required ...multi-objective optimization ... See full document

... an optimization problem involves only one objective function, the task of finding the optimal solution is called Single Objective ...Multi-Objective Optimization. Evolutionary Algorithms are ... See full document

... As we have said in the previous chapter, the sum-rate capacity of the multi-antenna Gaus- sian broadcast channel has recently been computed. However, the search for computation- ally efficient practical schemes that ... See full document

... Genetic algorithms are very effective and powerful search techniques that have been utilized successfully for solving practical problems in many disciplines such as engineering, business, and ... See full document

... Analog circuit synthesis is the process of designing and constructing a network to meet the multiple and complex performance specifications by the large number of design variables. Robust analog circuit design which ... See full document

... obtained using three methodologies: (i) an earlier proposed one critical constraint approach which ignored all other constraints, (ii) our approach with Ditlevson bounds but all constraints are considered and ... See full document

... maximal throughput in cellular networks without paying any fairness ...and throughput enhancement in customized ...maximal throughput for the case of two scheduled connections ...the ... See full document

... The results achieved are summarised in Table 1, with additional details provided as supplementary data. The minimum cost ach- ieved was £ 419,514 within 985,000 function evaluations for the population of 1,000, and £ ... See full document

... (Hosseininejad & Dadkhah, 2019) uses the cuckoo optimization algorithm to propose a new method which resolves the challenges of the planning of mobile robot path in a non-static environment. Moreover, the ... See full document

... To guide ANN learning, GA is employed to determine the best number of hidden layers and nodes, learning rate, momentum rate and weight optimization. With GA, it is proven that the learning becomes faster and ... See full document

... hybrid evolutionary algorithm to solve nonlinear partitional clustering ...The evolutionary algorithm is the combination of FAPSO (fuzzy adaptive particle swarm optimization), ACO (ant colony ... See full document

... of optimization problems and practical engineering ...multi-objective optimization problems as stated by Kundu et ...numerical optimization (Basak et ...an optimization model to minimize the ... See full document

... by using this comprehensive framework and solution approaches can achive the best performance includes minimum total costs and minimum of maximum travel time, and based on their organization directions can choose ... See full document

... Currently, using FNA as a method for tumor mass sampling and testing on that type of tumor (benign and malignant) is ...mining algorithms on the data obtained from the sampling, a higher accuracy can be ... See full document

... Relaying is a promising tool for expanding the network coverage area and increasing link reliability. Nowadays, there is a great interest in reducing the size of communica- tion tools, thereby reducing power sources and ... See full document

... 17 errors, tracking BDI and BDTI is far more challenging. Yet, the less accurate tracking perfor- mance of the physical market is not startling. It is a consequence of, first, the low correlation be- tween the physical ... See full document

... Genetic algorithm (GA) is an optimization method based on the mechanics of natural selection. In nature, weak and unfit species within their environment are faced with extinction by natural selection. The strong ... See full document

... them to be put into practice. There are many new concepts, design criteria,and scenarios that have been proposed for 5G; some of them, if implemented, willbring fundamental changes at the architectural and node level. ... See full document

... The Hyper-heuristics approach does not compete with problem-specific approaches, but to provide a general framework able to deliver solutions of a good quality for a wide range of optimization problems [5]. ... See full document