{ "info": { "author": "ildoonet", "author_email": "ildoo@ildoo.net", "bugtrack_url": null, "classifiers": [], "description": "This code is to solve traveling salesman problem by using simulated annealing meta heuristic.\r\n\r\n```\r\nimport numpy\r\nimport pytspsa\r\n\r\n\r\nsolver = pytspsa.Tsp_sa()\r\nc = [\r\n [0, 0],\r\n [0, 1],\r\n [0, 2],\r\n [0, 3]\r\n]\r\nc = numpy.asarray(c, dtype=numpy.float32)\r\nsolver.set_num_nodes(4)\r\nsolver.add_by_coordinates(c)\r\nsolver.set_t_v_factor(4.0)\r\n\r\n# solver.sa() or sa_auto_parameter() will solve the problem.\r\nsolver.sa_auto_parameter(12)\r\n\r\n# getting result\r\nsolution = solver.getBestSolution()\r\n\r\nprint('Length={}'.format(solution.getlength()))\r\nprint('Path= {}'.format(solution.getRoute()))\r\n```\r\n\r\nSee github page.", "description_content_type": null, "docs_url": null, "download_url": "UNKNOWN", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/ildoonet/simulated-annealing-for-tsp", "keywords": "tsp, optimization, simulated annealing, traveling salesman problem", "license": "UNKNOWN", "maintainer": "", "maintainer_email": "", "name": "pytspsa", "package_url": "https://pypi.org/project/pytspsa/", "platform": "x86_64", "project_url": "https://pypi.org/project/pytspsa/", "project_urls": { "Download": "UNKNOWN", "Homepage": "https://github.com/ildoonet/simulated-annealing-for-tsp" }, "release_url": "https://pypi.org/project/pytspsa/0.1.14/", "requires_dist": null, "requires_python": null, "summary": "Initial Release.", "version": "0.1.14" }, "last_serial": 2871276, "releases": { "0.1.14": [ { "comment_text": "", "digests": { "md5": "ef6c123358d2cc083aab50849f931273", "sha256": "1e10b6313ed8e98f1bf639d34aa7792d9689b22a4dd9c14990ee428fe24ad4ef" }, "downloads": -1, "filename": "pytspsa-0.1.14.tar.gz", "has_sig": false, "md5_digest": "ef6c123358d2cc083aab50849f931273", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 18626, "upload_time": "2017-05-13T10:08:04", "url": "https://files.pythonhosted.org/packages/ba/14/05e340c9e86e872d10ef41ff7d849bc25a72b3d9e52feb94ffee5eb9ca2c/pytspsa-0.1.14.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "ef6c123358d2cc083aab50849f931273", "sha256": "1e10b6313ed8e98f1bf639d34aa7792d9689b22a4dd9c14990ee428fe24ad4ef" }, "downloads": -1, "filename": "pytspsa-0.1.14.tar.gz", "has_sig": false, "md5_digest": "ef6c123358d2cc083aab50849f931273", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 18626, "upload_time": "2017-05-13T10:08:04", "url": "https://files.pythonhosted.org/packages/ba/14/05e340c9e86e872d10ef41ff7d849bc25a72b3d9e52feb94ffee5eb9ca2c/pytspsa-0.1.14.tar.gz" } ] }