1. INTRODUCTION Optimization, in simple terms, means minimize the cost incurred and maximize the profit such as resource utilization. EAs are population based metaheuristic (means optimize problem by iteratively trying to improve the solution with regards to the given measure of quality) optimization algorithms that often perform well on approximating solutions to all types of problem because they do not make any assumptions about the underlying evaluation of the fitness function. There are many EAs available viz. Genetic Algorithm (GA) [1] , Artificial Immune Algorithm (AIA) [2], Ant Colony Optimization (ACO) [3], Particle Swarm Optimization (PSO) [4], Differential Evolution (DE) [5, 6], Harmony Search (HS) [7], Bacteria Foraging Optimization (BFO) [8], Shuffled Frog Leaping (SFL) [9], Artificial Bee Colony (ABC) [10, 11], Biogeography-Based Optimization (BBO) [12], Gravitational Search Algorithm (GSA) [13], Grenade Explosion Method (GEM) [14] etc. To use any EA, a model of decision problem need to be built that specifies: 1) The decisions to be made, called decision variables, 2) The measure to be optimized, called the objective, and 3) Any logical restrictions on potential solutions, called constraints. These 3 parameters are necessary while building any optimization model. The solver will find values for the decision variables that satisfy the constraints while optimizing (maximizing or minimizing) the objective. But the problem with all the above EAs is that, to get optimal solution, besides the necessary parameters (explained above), many algorithms-specific parameters need to be handled appropriately. For example, in case of GA, adjustment of the algorithm-specific parameters such as crossover rate (or probability, PC), mu... ... middle of paper ... ... the algorithm are identified and modified suitably, using OpenMP, one can easily exploit the functionality of multi-core CPU and can maximize the utilization of all the cores of multi-core system which is necessary from the optimization point of view (which says, maximize the resource utilization). This paper contributes towards this direction and undertakes a detailed study by investigating the effect of number of cores, dimension size, population size, and problem complexity on the speed-up of TLBO algorithm. In the remainder of this paper, we give a brief literature review of TLBO and its applications. Thereafter, we discuss the possibilities of tweaking a TLBO to make it suitable for parallel implementation on a multi-core system. Then, we present results on few test problems of different complexities and show appreciable speed-ups using our proposed algorithm.
The Uncertainty Reduction Theory states that before and during initial interactions between two people, one's first instinct is to reduce uncertainty about the other through various methods. For example, when you see someone you think you would like to know, you try and figure out what they are like through various methods so you can control the conversation and steer it into a path that the other person finds interesting.
Helping Jessica to reach her narrative writing goals, Mrs. Tracy has several strategies at her disposal. Jessica’s joy of sharing her personal experiences and the ability to verbally express those idea is a strength that should be utilized. The POW and C.SPACE strategies discussed in the Star Sheets would be excellent tools for her to use to gather her thoughts in an orderly fashion. Her sample writing shows she has good ideas but little development and simple sentences. If Jessica is really overwhelmed by the writing task I would start her with a simple organizer to outline the beginning, middle, and end of her story (see attached organizer). Because Jessica is comfortable verbally tell her stories I would start by walking her through the
Genetic Algorithms provide a holistic search process based on principles of natural genetics and survivals of the fittest……
Nonexperimenal Design as there is no active or direct intervention. Research is simply looking at the validity of a test to identify problem swimmers.
Doing this research paper has given me more information and background knowledge about my topic. For the first part we had to write about what we knew, thought, and/or imagined. The second part was about the research. Having to do research about sexuality and how it is determined has made me understand that there is no right or wrong answer for it. Although, at the beginning I believed your sexuality was a choice. I was able to increase my understanding of the controversy of it being about genetics or more of a choice.
Weng, Y., Kuo, K.N., Yang, C., Lo, H., Chen, C., & Ya-Wen, C. (2013). Implementation
Living in a divided society based upon the religions of the Puritans and the Quakers, Evan Feversham sought out his own religious faith through his daily interactions with both religious groups.
During the World War II, the main issue of extreme importance was to maximize the efficiency of resources. The projects related to World War II required attention and obviously spread resources thin. Therefore, linear programming was developed to address this issue. Programming was used in military at that time to deal with activities such as planning schedules efficiently or optimizing the deploying of men. In 1947, George Dantzig, a U.S. Air Force member at that time, developed the Simplex optimization method. The aim was to provide an efficient algorithm for solving programming problems that had linear structures. Since then, the theory behind linear programming and its applications have been extensively developed by experts from a variety of fields, particularly mathematics and economics [49].
Kalyanasundaram, Kumaran. "SPEC HPG---SPEC HPG Benchmarks." Proceedings of the 2006 ACM/IEEE Conference on Supercomputing - SC '06 (2006): n. pag. Web.
It is optimized by using evidence-based, thoughtful approaches associated with performance technology, quality control, communications, organization / employee development, project management, business processes, human resources, instructional design, change management and strategic planning and many more.
Different objective functions generate different solutions even form the same evolutionary algorithm. Presuming also that the fitness could either be a minimization or a maximization function. Moreover, the algorithm could be formulated with one or with multi objective functions. To sum up, "choosing optimizati...
... al. (2011) gives a mixed integer programming (MIP) method which is useful for constructing orthogonal designs.
The development of linear programming has been ranked among the most important scientific advances of the mid 20th century. Its impact since the 1950’s has been extraordinary. Today it is a standard tool used by some companies (around 56%) of even moderate size. Linear programming uses a mathematical model to describe the problem of concern. Linear programming involves the planning of activities to obtain an optimal result, i.e., a result that reaches the specified goal best (according to the mathematical model) among all feasible alternatives.
Nowadays, there is a persistent demand for greater computational power to process large amount of data. HPC makes previously unachievable calculations possible. Today the modern computer architectures are relying more and more upon hardware level parallelism. They attain computing performance, through realization of multiple execution units, pipelined instructions [1] and multiple CPU cores [2]. The largest and fastest computers use both shared and distributed memory architectures. Contemporary trends show that the hybrid type of memory architectures will continue to prevail [3].
To be able to stop or at least decrease damages in the environment, Environmental management should be evident in the world. There are several different approaches to environmental management. For example, Eco profit. This approach focuses on protecting the environment through a systematic way, furthermore this approach is used all over the world and is one of the most basic approaches to environmental management. The next approach is human ecology approach. This type of approach studies the relationship of humans and nature. It tackles how humans can help the environment be better, by not harming nature. In most environmental management plans, it includes a certain model, called the Plan, Do, and Check. The first step is "Plan". In this step, companies