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It has become acceptable practice to use only a limit on the number of fitness function evaluations (FEs) as a stopping condition when comparing population-based optimization algorithms, irrespective of the initial number of candidate solutions. This practice has been advocated in a number of competitions to compare the performance of population-based algorithms, and has been used in many articles...
As a modern Evolutionary Algorithm, Differential Evolution (DE) is usually criticized for its slow convergence when compared to Particle Swarm Optimization (PSO) on the PSO’s benchmark functions. In this paper, by combing the merits of PSO and DE, we first present a new hybrid DE algorithm to accelerate its convergence speed. Then a novel mutation strategy with local and global search operators is...
This paper presents a hybrid metaheuristic for solving the Quadratic Assignment Problem (QAP). The proposed algorithm involves using the Greedy Randomized Adaptive Search Procedure (GRASP) to construct an initial solution, and then using a hybrid Simulated Annealing and Tabu Search (SA-TS) algorithm to further improve the solution. Experimental results show that the hybrid metaheuristic is able to...
OpenMP tasks propose a new dimension of concurrency to cap irregular parallelism within applications. The addition of OpenMP tasks allows programmers to express concurrency at a high level of abstraction and makes the OpenMP runtime responsible about the burden of scheduling parallel execution. The ability to observe the performance of OpenMP task scheduling strategies portably across shared memory...
The Schools of Education and Engineering and Computing Sciences at New York Institute of Technology collaborated to create a graduate certificate for K-12 STEM education described on NYIT's website http://www.nyit.edu/academics/stem/. The basic tenets of the 18-credit certificate program were Common Core State Standards for science, mathematics and technology [9], technology integration into instruction...
The goal of this research is to design a low cost cache replacement algorithm that achieves comparable performance to existing scheme. In previous work, we proposed an enhancement to the SLRU (Segmented LRU) algorithm called fixed SLRU that fixes the number of protected and probationary segments. Due to an ineffective simulation environment, we were unable to fully understand our results. In this...
In recent years Exchange Traded Funds has emerged as an important investment alternative that combines both the low risk and high liquidity advantages. The construction and active management of ETFs are the central issues for the exploitation of its potential. This paper conducts the empirical studies, using the Markowitz portfolio optimization model, to construct an optimal ETF portfolio in the emerging...
The ability of students in public speaking is a stated requirement for Electrical and Information Engineering students at all levels according to the Washington, Sydney and Dublin Accords and UK and European Qualifications standards. It is also a frequently cited requirement in job specifications for graduate engineers. Effective public speaking is a skill that can be assessed simply by observing...
This paper implements Standard Particle Swarm Optimization (PSO) and a new algorithm that aims to be better than the classical PSO. An m-file code is used to simulate the Standard Particle Swarm Optimization and it is evaluated using the five well known benchmark functions namely Sphere, Ackley, Rastrigin, Rosenbrock, and Shcwefel's Problem 2.26. A new PSO algorithm known as Gompertz increasing inertia...
In this paper, a naive particle swarm algorithm for constrained optimization problems is proposed. Also, a direct constraint handling method is adopted, which is more direct and easier to be implemented in comparison with other constraint handling methods, such as penalty function, etc. The experimental results on benchmark problems show that the proposed algorithm can solve constrained optimization...
This paper proposes a novel implementation of micro-Differential Evolution (μDE) that incorporates within the DE scheme an extra search move that attempts to improve the best solution by perturbing it along the axes. These extra moves complement the DE search logic and allows the exploration of the decision space from an alternative perspective. In addition, these extra moves at subsequent activations...
Evaluation of ambient assisted living (AAL) systems is particularly challenging due to the complexity of such systems and the variety of solutions adopted and services offered. Yet analyzing and comparing AAL solutions is paramount for assessing research results in this area. Evaluating AAL Systems through Competitive Benchmarking (EvAAL) is a recently established international competition that aims...
In recent years performance of High Performance Computing Clusters took precedence over their power consumption. However, costs of energy and demand for ecologically acceptable IT solutions are higher than ever before, therefore a need for HPC clusters with acceptable power consumption becomes increasingly important. Consequently, the Green500 list, which takes into account both performance and power...
In this letter, we propose an improved version of generalized eigenvalue proximal support vector machine (GEPSVM), called IGEPSVM for short. The main improvements are 1) the generalized eigenvalue decomposition is replaced by the standard eigenvalue decomposition, resulting in simpler optimization problems without the possible singularity. 2) An extra meaningful parameter is introduced, resulting...
In 2010 the Australian government commissioned the Australian Learning and Teaching Council (ALTC) to undertake a national project to facilitate disciplinary development of threshold learning standards. The aim was to lay the foundation for all higher education providers to demonstrate to the new national higher education regulator, the Tertiary Education Quality and Standards Agency (TEQSA), that...
Students often annotate texts they are reading using highlighting, underlining, and written comments and marks in the margins of the text. These may serve various functions and will reflect each student's goals and understanding of the text. This research proposes two simple biology-inspired approaches to represent the patterns of student annotations and to cluster students based on the similarity...
In this paper, A self-adaptive strategy to determine the control parameters of Differential Evolution (DE) is proposed based on the elaborate analysis of intrinsic structure. The projection information of fitness function in differential direction is used to get the scale factor, while the difference between the local distance and global search range is applied to determine the crossover rate. This...
Particle Swarm Optimization (PSO) is a stochastic optimization approach that originated from early attempts to simulate the behavior of birds looking for food. Estimation of distributions algorithms (EDAs) are a class of evolutionary algorithms that build and maintain a probabilistic model capturing the search space characteristics and continuously use this model to generate new individuals. In this...
Cooperative Coevolutionary Evolutionary Algorithm is an extension of conventional Evolutionary Algorithm: it implements the idea of divide and conquer by dividing the whole set of variables into several subsets (groups), and evolve each subset independently with a certain optimizer. How to group the variables effectively have been studied by several researchers. Quite a number of variable grouping...
At beginning of the search process of particle swarm optimization, one of the disadvantages is that PSO focuses on the global search while the local search is weakened. However, at the end of the search procedure, the PSO focuses on the local search as almost all the particles converge into small areas which could cause the particle swarm to be trapped in the local minima if no particle is found near...
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