{"group":{"id":1,"name":"Community","lockable":false,"created_at":"2012-01-18T18:02:15.000Z","updated_at":"2026-05-26T00:16:20.000Z","description":"Problems submitted by members of the MATLAB Central community.","is_default":true,"created_by":161519,"badge_id":null,"featured":false,"trending":false,"solution_count_in_trending_period":0,"trending_last_calculated":"2026-05-26T00:00:00.000Z","image_id":null,"published":true,"community_created":false,"status_id":2,"is_default_group_for_player":false,"deleted_by":null,"deleted_at":null,"restored_by":null,"restored_at":null,"description_opc":null,"description_html":null,"published_at":null},"problems":[{"id":638,"title":"Uniform binary crossover","description":"Given two binary vectors, return the two children by combining the genes of them using a binary crossover mask.\r\n\r\nMore information: \u003chttp://en.wikipedia.org/wiki/Crossover_(genetic_algorithm)#Uniform_Crossover_and_Half_Uniform_Crossover Uniform crossover\u003e\r\n\r\n* Parents and mask are row vectors of the same size _N_;\r\n* Output is a 2 x _N_ matrix containing both children;\r\n* The first child must have genes from the first parent at the positions where the mask is true, and genes from the second parent where the mask is false;\r\n* The second child must have genes from the first parent at the positions where the mask is false, and genes from the second parent where the mask is true;\r\n* The mask is also supplied.\r\n\r\nExample:\r\n\r\n  mask    = [1 0 0 0 1 1 1 0 0];\r\n  parent1 = [0 0 0 1 1 1 0 0 0];\r\n  parent2 = [1 1 0 0 1 0 1 1 0];\r\n  \r\n  children = [0 1 0 0 1 1 0 1 0;\r\n              1 0 0 1 1 0 1 0 0];\r\n","description_html":"\u003cp\u003eGiven two binary vectors, return the two children by combining the genes of them using a binary crossover mask.\u003c/p\u003e\u003cp\u003eMore information: \u003ca href=\"http://en.wikipedia.org/wiki/Crossover_(genetic_algorithm)#Uniform_Crossover_and_Half_Uniform_Crossover\"\u003eUniform crossover\u003c/a\u003e\u003c/p\u003e\u003cul\u003e\u003cli\u003eParents and mask are row vectors of the same size \u003ci\u003eN\u003c/i\u003e;\u003c/li\u003e\u003cli\u003eOutput is a 2 x \u003ci\u003eN\u003c/i\u003e matrix containing both children;\u003c/li\u003e\u003cli\u003eThe first child must have genes from the first parent at the positions where the mask is true, and genes from the second parent where the mask is false;\u003c/li\u003e\u003cli\u003eThe second child must have genes from the first parent at the positions where the mask is false, and genes from the second parent where the mask is true;\u003c/li\u003e\u003cli\u003eThe mask is also supplied.\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003emask    = [1 0 0 0 1 1 1 0 0];\r\nparent1 = [0 0 0 1 1 1 0 0 0];\r\nparent2 = [1 1 0 0 1 0 1 1 0];\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003echildren = [0 1 0 0 1 1 0 1 0;\r\n            1 0 0 1 1 0 1 0 0];\r\n\u003c/pre\u003e","function_template":"function children = uniform_crossover(mask,parent1,parent2)\r\n  children = [parent1;parent2];\r\nend","test_suite":"%%\r\nmask    = [1 0 0 0 1 1 1 0 0];\r\nparent1 = [0 0 0 1 1 1 0 0 0];\r\nparent2 = [1 1 0 0 1 0 1 1 0];\r\nchildren = [0 1 0 0 1 1 0 1 0;1 0 0 1 1 0 1 0 0];\r\nassert(isequal(uniform_crossover(mask,parent1,parent2),children))\r\n\r\n%%\r\nmask    = 1;\r\nparent1 = 1;\r\nparent2 = 0;\r\nchildren = [1;0];\r\nassert(isequal(uniform_crossover(mask,parent1,parent2),children))\r\n\r\n%%\r\nmask    = 1;\r\nparent1 = 1;\r\nparent2 = 0;\r\nchildren = [1;0];\r\nassert(isequal(uniform_crossover(mask,parent1,parent2),children))\r\n\r\n%%\r\nmask    = [1 1 1 0 1 0 1 1 0 0 0 0 0 1 0];\r\nparent1 = [0 1 1 1 1 0 0 0 0 1 0 0 1 0 1];\r\nparent2 = [0 1 1 0 1 0 1 0 1 0 1 1 0 1 1];\r\nchildren = [0 1 1 0 1 0 0 0 1 0 1 1 0 0 1;0 1 1 1 1 0 1 0 0 1 0 0 1 1 1]\r\nassert(isequal(uniform_crossover(mask,parent1,parent2),children))\r\n","published":true,"deleted":false,"likes_count":5,"comments_count":0,"created_by":3100,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":83,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-04-29T21:59:44.000Z","updated_at":"2026-05-26T03:27:48.000Z","published_at":"2012-04-29T21:59:49.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven two binary vectors, return the two children by combining the genes of them using a binary crossover mask.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMore information:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Crossover_(genetic_algorithm)#Uniform_Crossover_and_Half_Uniform_Crossover\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eUniform crossover\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eParents and mask are row vectors of the same size\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput is a 2 x\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e matrix containing both children;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe first child must have genes from the first parent at the positions where the mask is true, and genes from the second parent where the mask is false;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe second child must have genes from the first parent at the positions where the mask is false, and genes from the second parent where the mask is true;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe mask is also supplied.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[mask    = [1 0 0 0 1 1 1 0 0];\\nparent1 = [0 0 0 1 1 1 0 0 0];\\nparent2 = [1 1 0 0 1 0 1 1 0];\\n\\nchildren = [0 1 0 0 1 1 0 1 0;\\n            1 0 0 1 1 0 1 0 0];]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"}],"problem_search":{"problems":[{"id":638,"title":"Uniform binary crossover","description":"Given two binary vectors, return the two children by combining the genes of them using a binary crossover mask.\r\n\r\nMore information: \u003chttp://en.wikipedia.org/wiki/Crossover_(genetic_algorithm)#Uniform_Crossover_and_Half_Uniform_Crossover Uniform crossover\u003e\r\n\r\n* Parents and mask are row vectors of the same size _N_;\r\n* Output is a 2 x _N_ matrix containing both children;\r\n* The first child must have genes from the first parent at the positions where the mask is true, and genes from the second parent where the mask is false;\r\n* The second child must have genes from the first parent at the positions where the mask is false, and genes from the second parent where the mask is true;\r\n* The mask is also supplied.\r\n\r\nExample:\r\n\r\n  mask    = [1 0 0 0 1 1 1 0 0];\r\n  parent1 = [0 0 0 1 1 1 0 0 0];\r\n  parent2 = [1 1 0 0 1 0 1 1 0];\r\n  \r\n  children = [0 1 0 0 1 1 0 1 0;\r\n              1 0 0 1 1 0 1 0 0];\r\n","description_html":"\u003cp\u003eGiven two binary vectors, return the two children by combining the genes of them using a binary crossover mask.\u003c/p\u003e\u003cp\u003eMore information: \u003ca href=\"http://en.wikipedia.org/wiki/Crossover_(genetic_algorithm)#Uniform_Crossover_and_Half_Uniform_Crossover\"\u003eUniform crossover\u003c/a\u003e\u003c/p\u003e\u003cul\u003e\u003cli\u003eParents and mask are row vectors of the same size \u003ci\u003eN\u003c/i\u003e;\u003c/li\u003e\u003cli\u003eOutput is a 2 x \u003ci\u003eN\u003c/i\u003e matrix containing both children;\u003c/li\u003e\u003cli\u003eThe first child must have genes from the first parent at the positions where the mask is true, and genes from the second parent where the mask is false;\u003c/li\u003e\u003cli\u003eThe second child must have genes from the first parent at the positions where the mask is false, and genes from the second parent where the mask is true;\u003c/li\u003e\u003cli\u003eThe mask is also supplied.\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003emask    = [1 0 0 0 1 1 1 0 0];\r\nparent1 = [0 0 0 1 1 1 0 0 0];\r\nparent2 = [1 1 0 0 1 0 1 1 0];\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003echildren = [0 1 0 0 1 1 0 1 0;\r\n            1 0 0 1 1 0 1 0 0];\r\n\u003c/pre\u003e","function_template":"function children = uniform_crossover(mask,parent1,parent2)\r\n  children = [parent1;parent2];\r\nend","test_suite":"%%\r\nmask    = [1 0 0 0 1 1 1 0 0];\r\nparent1 = [0 0 0 1 1 1 0 0 0];\r\nparent2 = [1 1 0 0 1 0 1 1 0];\r\nchildren = [0 1 0 0 1 1 0 1 0;1 0 0 1 1 0 1 0 0];\r\nassert(isequal(uniform_crossover(mask,parent1,parent2),children))\r\n\r\n%%\r\nmask    = 1;\r\nparent1 = 1;\r\nparent2 = 0;\r\nchildren = [1;0];\r\nassert(isequal(uniform_crossover(mask,parent1,parent2),children))\r\n\r\n%%\r\nmask    = 1;\r\nparent1 = 1;\r\nparent2 = 0;\r\nchildren = [1;0];\r\nassert(isequal(uniform_crossover(mask,parent1,parent2),children))\r\n\r\n%%\r\nmask    = [1 1 1 0 1 0 1 1 0 0 0 0 0 1 0];\r\nparent1 = [0 1 1 1 1 0 0 0 0 1 0 0 1 0 1];\r\nparent2 = [0 1 1 0 1 0 1 0 1 0 1 1 0 1 1];\r\nchildren = [0 1 1 0 1 0 0 0 1 0 1 1 0 0 1;0 1 1 1 1 0 1 0 0 1 0 0 1 1 1]\r\nassert(isequal(uniform_crossover(mask,parent1,parent2),children))\r\n","published":true,"deleted":false,"likes_count":5,"comments_count":0,"created_by":3100,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":83,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-04-29T21:59:44.000Z","updated_at":"2026-05-26T03:27:48.000Z","published_at":"2012-04-29T21:59:49.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven two binary vectors, return the two children by combining the genes of them using a binary crossover mask.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMore information:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Crossover_(genetic_algorithm)#Uniform_Crossover_and_Half_Uniform_Crossover\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eUniform crossover\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eParents and mask are row vectors of the same size\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput is a 2 x\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e matrix containing both children;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe first child must have genes from the first parent at the positions where the mask is true, and genes from the second parent where the mask is false;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe second child must have genes from the first parent at the positions where the mask is false, and genes from the second parent where the mask is true;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe mask is also supplied.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[mask    = [1 0 0 0 1 1 1 0 0];\\nparent1 = [0 0 0 1 1 1 0 0 0];\\nparent2 = [1 1 0 0 1 0 1 1 0];\\n\\nchildren = [0 1 0 0 1 1 0 1 0;\\n            1 0 0 1 1 0 1 0 0];]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"}],"errors":[],"facets":[[],[{"value":"easy","count":1,"selected":false}]],"term":"tag:\"genetic algorithm\"","page":1,"per_page":50,"sort":"map(difficulty_value,0,0,999) asc"}}