The paper aims to propose Teaching Learning based Optimization (TLBO) algorithm to solve 3-D packing problem in containers. The objective which can be presented in a mathematical model is optimizing the space usage in a container. Besides the interaction effect between students and teacher, this algorithm also observes the learning process between students in the classroom which does not need any control parameters. Thus, TLBO provides the teachers phase and students phase as its main updating process to find the best solution. More precisely, to validate the algorithm effectiveness, it was implemented in three sample cases. There was small data which had 5 size-types of items with 12 units, medium data which had 10 size-types of items with 106 units, and large data which had 20 size-types of items with 110 units. Moreover, it was also compared with another algorithm called Gravitational Search Algorithm (GSA). According to the computational results in those example cases, it can be concluded that higher number of population and iterations can bring higher chances to obtain a better solution. Finally, TLBO shows better performance in solving the 3-D packing problem compared with GSA.
The investor needs to a clear strategy for the purpose of access to the financial market, that is, has a plan to increase The share of the profits thinking entrepreneur and new, and highlights the importance of this in that it sets for the investor when it goes to the market, and when it comes out of it, and at what price to buy or sell the stock, and what is the the amount of money it starts. Fortunately, he does not need to invent his own investment strategy, because over the years the development of effective methods of buying and selling, and once you understand how to work these methods investor can choose the most appropriate methods and adapted image that fit his style investment .
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... Show MoreThe performance in the 110-meter hurdles at the sprint hurdles event is determined by several physical and physiological qualities. Nonetheless, relatively little attention has been paid to the predictability of such factors in determining race performance. This study seeks to fill this gap by establishing the most critical physical and physiological characteristics affecting elite hurdlers’ performance and creating a statistical model that predicts race times from the identified measurable characteristics. The study utilized a descriptive research design in-volving six elite male hurdlers, all of whom completed a battery of standardized physical and functional tests to assess their explosive lower-body strength, agility, reaction
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