Search Results - (( developing decision problems algorithm ) OR ( java implication based algorithm ))
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An Efficient Ranking Analysis In Multi-Criteria Decision Making
Published 2017“…This study is conducted with the aims to develop a new ranking method for multi-criteria decision making problem with conflicting criteria. …”
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Application of a preference relationship in decision-making based on intuitionistic fuzzy soft sets
Published 2018“…In this paper, an adjustable algorithm is developed to handle the problem of group decision-making based on a preference relationship of IFSSs. …”
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DEVELOPMENT OF INTELLIGENT CONTROLLER FOR TRAFFIC LIGHTS WITH DYNAMIC PHASE ARRANGEMENT FOR SINGLE-ISOLATED INTERSECTIONS
Published 2014“…The first decision made by the controlling algorithm was the sequence priority. …”
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Some metaheuristic algorithms for solving multiple cross-functional team selection problems
Published 2022“…The developed method also demonstrated the effectiveness of the multi-criteria decision-making process when compared with the multi-objective evolutionary algorithm (MOEA). …”
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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective
Published 2023“…To integrate machine learning and human interactions, this paper develops a new three-stage interactive algorithm in business analytics, called the interactive Nautilus-based algorithm, to address complex problems. …”
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Development of location-inventory model based on all-unit quantity discount policy
Published 2011“…Therefore, the obtained results are expected to be suboptimal in many situations. To deal with this problem, in recent years, joint location-inventory models are developed to simultaneously determine the inventory control decisions and facility locations decision of a distribution network. …”
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Hybrid group decision making method based on multi-granular information using fusion algorithms and consistent fuzzy preference relation / Siti Amnah Mohd Ridzuan
Published 2017“…This will increase the complexity in computation. Two new decision making models have been developed in this study, the first is the combination of multi-granular linguistic information using fusion algorithm and consistent fuzzy preference relations (CFPR) and the second one is the combination of multi-granular uncertain linguistic information and consistent linguistic fuzzy preference relations (CLFPR) to cater this problem. …”
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Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin
Published 2024“…The project successfully achieves its predetermined objectives, culminating in the development of an effective Remote to Local (R2L) Intrusion Detection System utilizing the Decision Tree algorithm. …”
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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…Although useful, the existing algorithms does not provide any comparative data to select an algorithm based on the problem size and difficulty and the use of other neighborhood algorithms (including Great Deluge and Late Acceptance Hill Climbing) has not been sufficiently explored as well. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…Thus in this study we intend to overcome these problems by determining a feature subset and the number of the cluster problems after developing an algorithm which simultaneously solved these issues. …”
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Nature-Inspired Heuristic Frameworks Trends in Solving Multi-objective Engineering Optimization Problems
Published 2025“…Nowadays, nature-inspired artificial intelligent metaheuristic optimization algorithms (MHOAs) have gained many attentions from researchers all over the world due to their capabilities in solving various decision-making problems. …”
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The Parameter Reduction of the Interval-Valued Fuzzy Soft Sets and Its Related Algorithms
Published 2014“…To this end, an interval-valued fuzzy soft set (IVFSS) that combines soft set theory with interval-valued fuzzy set theory has been proposed to handle imprecision and uncertainty in applications such as decision-making problems. However, there has been little focus on parameter reduction of the interval-valued fuzzy soft sets, which is significant in decision-making problems. …”
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Supplier selection for contractors using Fuzzy TOPSIS Algorithm / Mohamed Shafiq Mohamed Yusof
Published 2020“…The future work of this project is to develop a system by using the same domain but with different algorithm and compare the result with the current result obtained from the system…”
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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…This condition impeded the entropy-based heuristic of existing ATM algorithm to develop effective decision boundaries due to its biasness towards the dominant class. …”
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An adjustable approach to multi-criteria group decision-making based on a preference relationship under fuzzy soft information
Published 2017“…In this regard, fuzzy soft model can be considered as an efficient tool in decision-making. To date, different algorithms have been proposed for solving collective decision-making problems based on fuzzy soft set theory. …”
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An integrated algorithm of analytical network process with case-based reasoning to support the selection of an ideal football team formation and players
Published 2021“…However, there are very few algorithms or decision engines available that could actually be used by decision-makers to aid in the process of forming a football team. …”
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Interval-valued fuzzy soft topology and its applications in group decision-making problems
Published 2022“…In this thesis, we develop two multi algorithms based on the interval-valued fuzzy soft topology to overcome different situations in decision-making problems. …”
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Modeling forest fires risk using spatial decision tree
Published 2011“…This paper presents our initial work in developing a spatial decision tree using the spatial ID3 algorithm and Spatial Join Index applied in the SCART (Spatial Classification and Regression Trees) algorithm. …”
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Development of bi-objective optimization model for supply chain network design using data envelopment analysis
Published 2017“…Moreover, in the second objective Benders decomposition algorithm has been introduced as an effective approach for large-scale size problem. …”
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