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            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering",
            "Topic :: Software Development"
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        "description": "# Bat Algorithm in Python\n\n## Objective\nThe main objective is to create an implementation of bat algorithm in Python programming language.\n\n## Installation\n\n    pip install BatAlgorithm\n\n### Example\nThe following example presents a simple use of bat algorithm. `Fun()` denotes the objective function that may be changed by the user. Control parameters should be defined within `BatAlgorithm()` constructor. Order of parameters is as\nfollows: `BatAlgorithm(D, NP, N_Gen, A, r, Qmin, Qmax, Lower, Upper, function)` where:\n\n- `D`  denotes dimension of the problem,\n- `NP` denotes population size,\n- `N_Gen`  denotes number of generations (iterations),\n- `A` parameter denotes loudness,\n- `r` parameter denotes pulse rate,\n- `Qmin` parameter denotes frequency minimum,\n- `Qmax` parameter denotes frequency maximum,\n- `Lower` denotes lower bound,\n- `Upper` denotes upper bound and\n- `function` passes objective function.\n\n## CODE EXAMPLE:\n\n```python\nimport random\nfrom BatAlgorithm import *\n\ndef Fun(D, sol):\n    val = 0.0\n    for i in range(D):\n        val = val + sol[i] * sol[i]\n    return val\n\n# For reproducive results\n#random.seed(5)\n\nfor i in range(10):\n    Algorithm = BatAlgorithm(10, 40, 1000, 0.5, 0.5, 0.0, 2.0, -10.0, 10.0, Fun)\n    Algorithm.move_bat()\n```\n\n## Bugs\nBugs and extension should be send via Github.\n\n## Authors\nIztok Fister Jr. and Marko Burjek\n\n## References\n\nYang, X.-S. \"A new metaheuristic bat-inspired algorithm.\" Nature inspired cooperative strategies for optimization (NICSO 2010). Springer\nBerlin Heidelberg, 2010. 65-74.\n\nFister, I. Jr., Fister, I., Yang, X.-S., Fong, S., Zhuang, Y. \"Bat algorithm: Recent advances.\" IEEE 15th International Symposium on Computational Intelligence and Informatics (CINTI), IEEE, 2014. 163-167.",
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