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49 results on '"Vasant, Pandian M."'

2. Application of Artificial Intelligence for Reservoir Storage Prediction: A Case Study

Author

Azad, Abdus Samad, Vasant, Pandian M., Gámez Vintaned, José A., Watada, Junzo, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Ibrahim, Rosdiazli, editor, K. Porkumaran, editor, Kannan, Ramani, editor, Mohd Nor, Nursyarizal, editor, and S. Prabakar, editor

Published
2022
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22. Quantum-Based Analytical Techniques on the Tackling of Well Placement Optimization.

Author

Islam, Jahedul, Mamo Negash, Berihun, Vasant, Pandian M., Ishtiaque Hossain, Nafize, and Watada, Junzo

Subjects
SHALE gas reservoirs, PARTICLE swarm optimization, GAS wells, MATHEMATICAL optimization, ALGORITHMS
Abstract

The high dimensional, multimodal, and discontinuous well placement optimization is one of the main difficult factors in the development process of conventional as well as shale gas reservoir, and to optimize this problem, metaheuristic techniques still suffer from premature convergence. Hence, to tackle this problem, this study aims at introducing a dimension-wise diversity analysis for well placement optimization. Moreover, in this article, quantum computational techniques are proposed to tackle the well placement optimization problem. Diversity analysis reveals that dynamic exploration and exploitation strategy is required for each reservoir. In case studies, the results of the proposed approach outperformed all the state-of-the-art algorithms and provided a better solution than other algorithms with higher convergence rate, efficiency, and effectiveness. Furthermore, statistical analysis shows that there is no statistical difference between the performance of Quantum bat algorithm and Quantum Particle swarm optimization algorithm. Hence, this quantum adaptation is the main factor that enhances the results of the optimization algorithm and the approach can be applied to locate wells in conventional and shale gas reservoir. [ABSTRACT FROM AUTHOR]

Published
2020
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31. Hybrid Optimization Techniques for Industrial Production Planning : Ph. D. Thesis, Dec 2008

Author

Vasant, Pandian M.

Subjects
Optimization, Hybrid systems, Ciencias Informáticas
Abstract

In this Ph. D thesis, the main significant contributions are: formulation of a new non-linear membership function using fuzzy approach to capture and describe vagueness in the technological coefficients of constraints in the industrial production planning problems. This non-linear membership function is flexible and convenience to the decision makers in their decision making process. Secondly, a nonlinear objective function in the form of cubic function for fuzzy optimization problems is successfully solved by 15 hybrid and non-hybrid optimization techniques from the area of soft computing and classical approaches. Among the 15 techniques, three outstanding techniques are selected based on the percentage of quality solution. An intelligent performance analysis table is tabulated to the convenience of decision makers and implementers to select the niche optimization techniques to apply in real word problem solving approach particularly related to industrial engineering problems., Facultad de Informática

Published
2010

33. A comprehensive review on theoretical framework-based electric vehicle consumer adoption research.

Author

Adnan, Nadia, Nordin, Shahrina Md, Rahman, Imran, Vasant, Pandian M., and Noor, Amir

Subjects
ELECTRIC vehicles, GREENHOUSE gas mitigation, AUTOMOBILE industry & the environment, FOSSIL fuels, CARBON offsetting
Abstract

Green vehicles, such as electric vehicles (EVs), are getting noteworthy popularity among consumers worldwide. The purpose of this paper is to establish EVs as a feasible long-term solution for the future of technology in the vehicle industry, which can decrease the current dependency on fossil fuels and also decrease greenhouse gas (GHG) emissions. As a part of long-term benefits, the adoption of EVs gives environmentally friendly innovation to society. Despite positive environmental implications, the total number of EVs in usage is still inadequate. One of the major causes of this insubstantial adoption of EVs is largely dependent on the perceptions of consumers regarding EVs. However, this particular research study offers an inclusive outline on the existing hurdles for consumer adoption of EVs as well as a framework of the theoretical standpoints that were developed for the adoption behaviour, in addition to considering consumer intentions in the direction of EVs. In this particular study, the researcher found that the literature regarding EV adoption tried to address only the diffusion method of EVs. Whereas this study highlights consumer innovations, which provides a wide insight on consumer emotions to overlook the major aspect in consumer EVs' adoption research. The theme of this particular literature can be implemented in order to better understand the consumers' emotions and behaviour towards the adoption of EVs. The scholars further stated that there is a possible cause for more recent developments within the technological adoption part that can assist to be a standard for upcoming developments. For the last few years, knowledge regarding the problems surrounding the adoption and diffusion of EVs has gained less attention. This study expands this line of research by focusing on making a chance for developing the theoretical frameworks in terms of adding emotions in a psychological perspective where consumer behaviour and ethics are considered. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Published
2017
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38. Hybrid pattern search and simulated annealing for fuzzy production planning problems

Author

Vasant, Pandian M., Nader Nassif Barsoum, Vasant, Pandian M., and Nader Nassif Barsoum

Abstract

In this paper, the hybridization of PS (Pattern Search) method and SA (Simulated Annealing) are incorporated in the optimization process. This is in order to look for the global optimal solution for the fitness function and decision variables as well as minimum computational CPU time. The real strength of SA approach has been tested in a case study problem of industrial production planning. This is due to the great advantage of SA for being easily escaping from trapped in local minima by accepting up-hill move through a probabilistic procedure in the final stages of optimization process. In the Ph.D. Thesis by Vasant (2008) [4], 16 different techniques were provided of heuristic and meta-heuristic approaches in solving industrial production problems with nonlinear cubic objective functions, eight decision variables and 29 constraints. In this paper, fuzzy technological problems have been solved using hybrid techniques of pattern search and simulated annealing (HSAPS). The simulated and computational results are compared to other various evolutionary techniques.

Published
2010

39. Hybrid general pattern search and simulated annealing for industrail production planning problems

Author

Nader Nassif Barsoum, Vasant, Pandian M., Nader Nassif Barsoum, and Vasant, Pandian M.

Abstract

In this paper, the hybridization of GPS (General Pattern Search) method and SA (Simulated Annealing) incorporated in the optimization process in order to look for the global optimal solution for the fitness function and decision variables as well as minimum computational CPU time. The real strength of SA approach been tested in this case study problem of industrial production planning. This is due to the great advantage of SA for being easily escaping from trapped in local minima by accepting up-hill move through a probabilistic procedure in the final stages of optimization process. Vasant [1] in his Ph. D thesis has provided 16 different techniques of heuristic and meta-heuristic in solving industrial production problems with non-linear cubic objective functions, eight decision variables and 29 constraints. In this paper, fuzzy technological problems have been solved using hybrid techniques of general pattern search and simulated annealing. The simulated and computational results are compared to other various evolutionary techniques.

Published
2010

44. Decision making in industrial production planning using fuzzy linear programming

Author

Vasant, Pandian M., Nagarajan, Ramachandran, Sazali Yaacob, Vasant, Pandian M., Nagarajan, Ramachandran, and Sazali Yaacob

Abstract

Any modern industrial manufacturing unit inevitably faces problems of vagueness in various aspects such as raw material availability, human resource availability, processing capability and constraints and limitations imposed by the marketing department. Such a complex problem of vagueness and uncertainty can be handled by the theory of fuzzy logic. In this paper, a new fuzzy logic based methodology using a S-curve membership function is used to solve a fuzzy mix product selection problem in industrial engineering. Profits and satisfaction levels have been computed using a fuzzy linear programming approach. Since there are several decisions to be taken, a performance measure has been defined to identify the decision that achieves a high level of profit with a high degree of satisfaction.

Published
2004

49. Hybrid Mesh Adaptive Direct Search and Genetic Algorithms for solving fuzzy non-linear optimization problems.

Author

Vasant, Pandian M.

Abstract

In this paper, computational and simulation results are presented for the performance of the fitness function, decision variables and CPU time of the proposed hybridization method of Mesh Adaptive Direct Search (MADS) and Genetic Algorithm (GA). MADS is a class of direct search algorithms for nonlinear optimization. The MADS algorithm is a modification of the Pattern Search (PS) algorithm. The algorithms differ in how the set of points forming the mesh is computed. The PS algorithm uses fixed direction vectors, whereas the MADS algorithm uses random selection of vectors to define the mesh. A key advantage of MADS over PS is that local exploration of the space of variables is not restricted to a finite number of directions (poll directions). This is the primary drawback of PS algorithms, and therefore the main motivation in using MADS to solve the industrial production planning problem is to overcome this restriction. A thorough investigation on hybrid MADS and GA is performed for the quality of the best fitness function, decision variables and computational CPU time. [ABSTRACT FROM PUBLISHER]

Published
2011
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