Metadata-Version: 2.1
Name: dynamic-moops
Version: 0.0.1.dev0
Summary: A mathematical implementation of dynamic MOO problems for a practical problem typically involving conflicting objectives.
Author: shark-utilities developers
Author-email: neuralNOD@outlook.com
Project-URL: Org. Homepage, https://github.com/sharkutilities
Keywords: dynamic,multi-objective,optimization,data science,data analysis,data scientist,data analyst,statistics
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: Unix
Classifier: Operating System :: POSIX
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.8
Description-Content-Type: text/markdown

<h1 align = "center">dynMOOPs</h1>

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A mathematical implementation of the classical **Dynamic Multi-Objective Optimization Problems (`dynMOOPs`)** for practical problems
that typically involves a set of conflicting objectives. In addition, the method allows penalty on premiumization (typically for costing) and
appreciations (typically for objectives involving maximization) methods for control.

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