The effect of job satisfaction on the relationship between organizational culture and organizational performance
Meta-heuristic algorithms have become popular in finding optimal solutions for nonlinear complex problems. These algorithms belong to stochastic and nondeterministic classes, have some problems with exploration or exploitation. The researchers used different strategies to tackle these issues. The...
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| Format: | Thesis |
| Language: | English English English |
| Published: |
2023
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/11044/1/24p%20MUHAMMAD%20IMRAN.pdf http://eprints.uthm.edu.my/11044/2/MUHAMMAD%20IMRAN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/11044/3/MUHAMMAD%20IMRAN%20WATERMARK.pdf |
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| Summary: | Meta-heuristic algorithms have become popular in finding optimal solutions for
nonlinear complex problems. These algorithms belong to stochastic and nondeterministic
classes, have some problems with exploration or exploitation. The
researchers used different strategies to tackle these issues. The flower pollination
algorithm (FPA) is one of the more popular nature-inspired search algorithms. It has
powerful global searchability to find the best optimal solution of real-world problems
by using levy flight to explore the search space. Moreover, its single tuning parameter
and simple mathematical model make it easier to implement. However, the flower
pollination algorithm has a few drawbacks which are partially addressed by the
practitioners. The first issue is regarding the balance between global pollination and
local pollination, which may negatively affect the optimality of solution. Secondly, the
FPA has a diversification problem which may leads to premature convergence of the
optimal solution. This research proposed an algorithm which is based on dynamic
switch probability to control the balance between exploration and exploitation which
increases its searchability. The swap operator has been added in local pollination to
enhance the exploitation behavior of pollens during the pollination process.
Furthermore, it is hybridized with the Pattern Search algorithm to ensure the optimality
of the solution. The performance of the proposed algorithm (IFPDSO-PS) has been
evaluated on seventeen standard test functions and compared with the stated metaheuristic
algorithms. The statistical tools (Absolute Mean Error & Fried Man) are used
to rank the performance of all algorithms. The proposed algorithm is ranked first
among the stated algorithms with respect to its performance in getting the optimal
solution |
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