The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
A. Charan Kumari - One of the best experts on this subject based on the ideXlab platform.
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Hyper-Heuristic Approach for service composition in internet of things
Electronic Government an International Journal, 2018Co-Authors: Neeti Kashyap, A. Charan KumariAbstract:The state-of-the-art on internet of things (IoT), deals with its definition, its architecture, ontology of its components, networking and middleware. IoT contains a large number of devices which are placed around the world. Every device provides an IoT service. As devices joining the IoT are increasing, the services are also rising proportionately. In order to meet the user requirements for the complex application, we need a collection of suitable services, also known as service composition. Identifying the optimal service composition in IoT is a challenging task. This paper presents a hyper-Heuristic Approach, a latest trend in the field of stochastic optimisation, for the solution of service composition problem in internet of things. The efficacy of the hyper-Heuristic Approach is tested on 25 test data instances and the results are compared with genetic algorithm, the most widely used global optimisation technique.
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Hyper-Heuristic Approach for multi-objective software module clustering
Journal of Systems and Software, 2016Co-Authors: A. Charan Kumari, K. SrinivasAbstract:Efficacy of hyper-Heuristic Approach for module clustering was studied.Hyper-Heuristic Approach is effective in identifying "high quality" clusters.Hyper-Heuristic Approach is "fast" enough to reach out to the optimum.User-friendly framework for software module clustering is presented. In the software maintenance phase of software development life cycle, one of the main concerns of software engineers is to group the modules into clusters with maximum cohesion and minimum coupling.To analyze the efficacy of Multi-objective Hyper-Heuristic Evolutionary Algorithm (MHypEA) in solving real-world clustering problems and to compare the results with the reported results in the literature for single as well as multi-objective formulations of the problem and also to present a CASE tool that assists software engineers in software module clustering process.The paper reports on empirical evaluation of the performance of MHypEA with the reported results in the literature. The comparison is mainly based on two factors - quality of the obtained solutions and the computational effort.On all the attempted problems, MHypEA reported good results in comparison to all the studies that were reported on multi-objective formulation of the problem, with a computational effort of nearly one-twentieth of the computational effort required by the other multi-objective algorithms.The hyper-Heuristic Approach is able to produce high quality clustered systems with less computational effort.
Meng Dong - One of the best experts on this subject based on the ideXlab platform.
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a Heuristic Approach to logistics network design for end of lease computer products recovery
Transportation Research Part E-logistics and Transportation Review, 2008Co-Authors: Derhorng Lee, Meng DongAbstract:Abstract This paper discusses the logistics network design for end-of-lease computer products recovery by developing a deterministic programming model for systematically managing forward and reverse logistics flows. Due to the complexity of such network design problem, a two-stage Heuristic Approach is developed to decompose the integrated design of the distribution networks into a location–allocation problem and a revised network flow problem. The applicability of the proposed method is illustrated in a numerical study. Computational experiments demonstrate that high-quality solutions are obtained while modest computational overheads are incurred.
Serge Domenech - One of the best experts on this subject based on the ideXlab platform.
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Fuzzy Heuristic Approach for sharp separation sequence synthesis
Computers & Chemical Engineering, 1994Co-Authors: Pascal Floquet, Luc Pibouleau, S. Aly, Serge DomenechAbstract:Abstract In this paper, a fuzzy Heuristic Approach based on the fuzzification of two Heuristic rules is presented for synthesizing sharp multicomponent separation sequences. The proposed procedure combines the values of the estimate separation mass load coefficients and the difference in normal boiling points of the components in a fuzzy rule based procedure. This Approach is illustrated with several examples with 4, 5, 7 and 8-component mixtures to be separated and its efficiency is compared with methods taken from literature.
D. Y. Sha - One of the best experts on this subject based on the ideXlab platform.
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Heuristic Approach for solving the multi-objective facility layout problem
International Journal of Production Research, 2005Co-Authors: C.-w. Chen, D. Y. ShaAbstract:A new Heuristic Approach for the generation of preferred objective weights to solve the multi-objective facility layout problem is presented. By applying a multi-pass halving and doubling procedure, a paired comparison method based on the strength of preference among objectives given by the decision-maker is developed. Furthermore, a ‘prior test’ is proposed to examine the consistency of the paired comparison matrix. An efficient method to transform the inconsistent matrix into a consistent one so the result can closely approximate the decision-maker's original assessments is also offered. The geometric mean method is then employed to obtain the objective weights and the final solution. There are five phases in the proposed Heuristic Approach. The first generates a basic solution; the second involves constructing a paired comparison matrix by using the multi-pass halving and doubling procedure; the third identifies the consistency of the paired comparison matrix; the fourth transforms the inconsistent mat...
K. Srinivas - One of the best experts on this subject based on the ideXlab platform.
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Hyper-Heuristic Approach for multi-objective software module clustering
Journal of Systems and Software, 2016Co-Authors: A. Charan Kumari, K. SrinivasAbstract:Efficacy of hyper-Heuristic Approach for module clustering was studied.Hyper-Heuristic Approach is effective in identifying "high quality" clusters.Hyper-Heuristic Approach is "fast" enough to reach out to the optimum.User-friendly framework for software module clustering is presented. In the software maintenance phase of software development life cycle, one of the main concerns of software engineers is to group the modules into clusters with maximum cohesion and minimum coupling.To analyze the efficacy of Multi-objective Hyper-Heuristic Evolutionary Algorithm (MHypEA) in solving real-world clustering problems and to compare the results with the reported results in the literature for single as well as multi-objective formulations of the problem and also to present a CASE tool that assists software engineers in software module clustering process.The paper reports on empirical evaluation of the performance of MHypEA with the reported results in the literature. The comparison is mainly based on two factors - quality of the obtained solutions and the computational effort.On all the attempted problems, MHypEA reported good results in comparison to all the studies that were reported on multi-objective formulation of the problem, with a computational effort of nearly one-twentieth of the computational effort required by the other multi-objective algorithms.The hyper-Heuristic Approach is able to produce high quality clustered systems with less computational effort.