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RISS 인기검색어
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- 저자 : Tawhid (검색결과 4 건)
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Tawhid, Mohamed A.,Savsani, Vimal Society for Computational Design and Engineering 2018 Journal of computational design and engineering Vol.5 No.1
In this paper, an effective ${\epsilon}$-constraint heat transfer search (${\epsilon}$-HTS) algorithm for the multi-objective engineering design problems is presented. This algorithm is developed to solve multi-objective optimization problems by evaluating a set of single objective sub-problems. The effectiveness of the proposed algorithm is checked by implementing it on multi-objective benchmark problems that have various characteristics of Pareto front such as discrete, convex, and non-convex. This algorithm is also tested for several distinctive multi-objective engineering design problems, such as four bar truss problem, gear train problem, multi-plate disc brake design, speed reducer problem, welded beam design, and spring design problem. Moreover, the numerical experimentation shows that the proposed algorithm generates the solution to represent true Pareto front.
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Improvement in DRX Power Saving for Non-real-time Traffic in LTE
Mohammad Tawhid Kawser,Mohammad Rakibul Islam,Khondoker Ziaul Islam,Mohammad Atiqul Islam,Mohammad Mehadi Hassan,Zobayer Ahmed,Rafid Hasan 한국전자통신연구원 2016 ETRI Journal Vol.38 No.4
A discontinuous reception (DRX) operation is included in the Long Term Evolution (LTE) system to achieve power saving and prolonged battery life of the user equipment. An improvement in DRX power saving usually leads to a potential increase in the packet delay. An optimum DRX configuration depends on the current traffic, which is not easy to estimate accurately, particularly for non-real-time applications. In this paper, we propose a novel way to vary the DRX cycle length, avoiding a continuous estimation of the data traffic when only non-real-time applications are running with no active real-time applications. Because a small delay in non-real-time traffic does not essentially impact the user’s experience adversely, we deliberately allow a limited amount of delay in our proposal to attain a significant improvement in power saving. Our proposal also improves the delay in service resumption after a long period of inactivity. We use a stochastic analysis assuming an M/G/1 queue to validate this improvement.
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Mohamed A. Tawhid,Vimal Savsani 한국CDE학회 2018 Journal of computational design and engineering Vol.5 No.1
In this paper, an effective ∊-constraint heat transfer search (e-HTS) algorithm for the multi-objective engineering design problems is presented. This algorithm is developed to solve multi-objective optimization problems by evaluating a set of single objective sub-problems. The effectiveness of the proposed algorithm is checked by implementing it on multi-objective benchmark problems that have various characteristics of Pareto front such as discrete, convex, and non-convex. This algorithm is also tested for several distinctive multi-objective engineering design problems, such as four bar truss problem, gear train problem, multi-plate disc brake design, speed reducer problem, welded beam design, and spring design problem. Moreover, the numerical experimentation shows that the proposed algorithm generates the solution to represent true Pareto front.
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Abdelmonem M. Ibrahim,Mohamed A. Tawhid 한국CDE학회 2019 Journal of computational design and engineering Vol.6 No.3
In this study, we propose a new hybrid algorithm consisting of two meta-heuristic algorithms; Differential Evolution (DE) and the Monarch Butterfly Optimization (MBO). This hybrid is called DEMBO. Both of the meta-heuristic algorithms are typically used to solve nonlinear systems and uncon-strained optimization problems. DE is a common metaheuristic algorithm that searches large areas of candidate space. Unfortunately, it often requires more significant numbers of function evaluations to get the optimal solution. As for MBO, it is known for its time-consuming fitness functions, but it traps at the local minima. In order to overcome all of these disadvantages, we combine the DE with MBO and propose DEMBO which can obtain the optimal solutions for the majority of nonlinear systems as well as unconstrained optimization problems. We apply our proposed algorithm, DEMBO, on nine different, unconstrained optimization problems and eight well-known nonlinear systems. Our results, when com-pared with other existing algorithms in the literature, demonstrate that DEMBO gives the best results for the majority of the nonlinear systems and unconstrained optimization problems. As such, the experimen-tal results demonstrate the efficiency of our hybrid algorithm in comparison to the known algorithms.
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