{"id":2350,"date":"2024-04-10T13:43:53","date_gmt":"2024-04-10T13:43:53","guid":{"rendered":"https:\/\/jita-au.com\/?p=2350"},"modified":"2024-04-29T12:43:40","modified_gmt":"2024-04-29T12:43:40","slug":"hybrid-methodology-of-nonlinear-goal-programming","status":"publish","type":"post","link":"https:\/\/jita-au.com\/index.php\/2024\/04\/10\/hybrid-methodology-of-nonlinear-goal-programming\/","title":{"rendered":"Hybrid Methodology of Nonlinear Goal Programming"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"2350\" class=\"elementor elementor-2350\" data-elementor-settings=\"{&quot;ha_cmc_init_switcher&quot;:&quot;no&quot;}\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-e232701 elementor-section-height-min-height elementor-section-full_width elementor-hidden-tablet elementor-hidden-mobile elementor-section-height-default elementor-section-items-middle wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no\" data-id=\"e232701\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;_ha_eqh_enable&quot;:false}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-cb97594\" data-id=\"cb97594\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a18c791 elementor-widget__width-inherit ha-has-bg-overlay elementor-widget elementor-widget-heading\" data-id=\"a18c791\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Vol. 4 No. 2 (2014): JITA - APEIRON<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b2fff26 elementor-widget elementor-widget-heading\" data-id=\"b2fff26\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><b>Lazo Rolji\u0107<b><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-52044bb elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"52044bb\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1c82606 elementor-widget elementor-widget-heading\" data-id=\"1c82606\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Hybrid Methodology of Nonlinear Goal Programming<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c297c9e elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"c297c9e\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-888860b e-grid e-con-full wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no e-con e-parent\" data-id=\"888860b\" data-element_type=\"container\" data-settings=\"{&quot;_ha_eqh_enable&quot;:false}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1841615 elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"1841615\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Original scientific paper<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-37a8d82 elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"37a8d82\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">DOI: https:\/\/doi.org\/10.7251\/JIT1402068R<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2f3b63f elementor-align-center elementor-widget elementor-widget-button\" data-id=\"2f3b63f\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/jita-au.com\/wp-content\/uploads\/2024\/04\/1635-Article-Text-3647-1-10-20150108.pdf\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Download Article PDF<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cb7c4cb elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"cb7c4cb\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-61aebe3 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"61aebe3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>What we demonstrate here is a nonlinear goal-programming (NGP) algorithm based on hybrid connection of the modified simplex method of goal programming, gradient method of feasible directions and method of optimal displacement size finding-called HNGPM. Iterative methodology is given in five steps: (1) linearization the set of nonlinear constraints at particular point, (2) solving the problem of normalized linear goal programming, (3) feasible direction computation, (4) calculating optimal step length displacement, and (5) testing out convergence problem. Our idea was to apply Euler\u2019s theorem for the \u201ctotal\u201d linearization of the nonlinear constraints (in the space) around particular point. According to Euler\u2019s theorem, it is possible to apply this methodology to solve the problems of NGP whether the nonlinear constraint functions are linearly or positively homogeneous.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5c5f19e elementor-widget elementor-widget-heading\" data-id=\"5c5f19e\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Keywords: Non-linear  goal  programming,  Cobb-  Douglas\u2019s  production  function,  Euler\u2019s  homogeneous  function  theorem,  feasible directions method.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6dd494a wpr-logo-position-center elementor-widget elementor-widget-wpr-logo\" data-id=\"6dd494a\" data-element_type=\"widget\" data-widget_type=\"wpr-logo.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\n\t\t\t<div class=\"wpr-logo elementor-clearfix\">\n\n\t\t\t\t\t\t\t\t<picture class=\"wpr-logo-image\">\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/jita-au.com\/wp-content\/uploads\/2024\/03\/cc-by-1.png\" alt=\"\">\n\n\t\t\t\t\t\t\t\t\t\t\t<a class=\"wpr-logo-url\" rel=\"home\" aria-label=\"\" href=\"https:\/\/jita-au.com\/\"><\/a>\n\t\t\t\t\t\t\t\t\t<\/picture>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t<a class=\"wpr-logo-url\" rel=\"home\" aria-label=\"\" href=\"https:\/\/jita-au.com\/\"><\/a>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cb049d1 elementor-widget elementor-widget-shortcode\" data-id=\"cb049d1\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\"><div class=\"post-views content-post post-2350 entry-meta load-static\">\r\n\t\t\t\t<span class=\"post-views-icon dashicons dashicons-chart-bar\"><\/span> <span class=\"post-views-label\">Post Views:<\/span> <span class=\"post-views-count\">641<\/span>\r\n\t\t\t<\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-511d0df elementor-section-height-min-height elementor-section-full_width elementor-hidden-mobile elementor-hidden-desktop elementor-hidden-laptop elementor-section-height-default elementor-section-items-middle wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no\" data-id=\"511d0df\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;_ha_eqh_enable&quot;:false}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-0acee9c\" data-id=\"0acee9c\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c0e98b3 elementor-widget__width-inherit ha-has-bg-overlay elementor-widget elementor-widget-heading\" data-id=\"c0e98b3\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Vol. 26 No. 2 (2023): JITA - APEIRON<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e6b43c5 elementor-widget elementor-widget-heading\" data-id=\"e6b43c5\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><strong>Igor Shubinsky, <\/strong>\n<strong> Alexey Ozerov<\/strong><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-68f1849 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"68f1849\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-186a6b2 elementor-widget elementor-widget-heading\" data-id=\"186a6b2\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7b2f501 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"7b2f501\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5027126 elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"5027126\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Original scientific paper<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4a5312c elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"4a5312c\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">DOI: <a href=\"http:\/\/localhost\/mytestingsite\/wp-content\/uploads\/2024\/02\/PVTC-Technical-Requirements.pdf\" target=\"_blank\" rel=\"noopener\">https:\/\/doi.org\/10.7251\/JIT2302061S<\/a><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8d7a912 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"8d7a912\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/jita-au.com\/wp-content\/uploads\/2024\/03\/10430-Article-Text-23890-1-10-20240103.pdf\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Download Article PDF<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-580ffd3 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"580ffd3\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-211717e elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"211717e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers\u2019 expenditures.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-62b72c3 elementor-widget elementor-widget-heading\" data-id=\"62b72c3\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f4dcd16 wpr-logo-position-center elementor-widget elementor-widget-wpr-logo\" data-id=\"f4dcd16\" data-element_type=\"widget\" data-widget_type=\"wpr-logo.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\n\t\t\t<div class=\"wpr-logo elementor-clearfix\">\n\n\t\t\t\t\t\t\t\t<picture class=\"wpr-logo-image\">\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/jita-au.com\/wp-content\/uploads\/2024\/03\/cc-by-1.png\" alt=\"\">\n\n\t\t\t\t\t\t\t\t\t\t\t<a class=\"wpr-logo-url\" rel=\"home\" aria-label=\"\" href=\"https:\/\/jita-au.com\/\"><\/a>\n\t\t\t\t\t\t\t\t\t<\/picture>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t<a class=\"wpr-logo-url\" rel=\"home\" aria-label=\"\" href=\"https:\/\/jita-au.com\/\"><\/a>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0f73093 elementor-widget elementor-widget-shortcode\" data-id=\"0f73093\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\"><div class=\"post-views content-post post-2350 entry-meta load-static\">\r\n\t\t\t\t<span class=\"post-views-icon dashicons dashicons-chart-bar\"><\/span> <span class=\"post-views-label\">Post Views:<\/span> <span class=\"post-views-count\">641<\/span>\r\n\t\t\t<\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-2d980b8 elementor-section-height-min-height elementor-section-full_width elementor-hidden-tablet elementor-hidden-desktop elementor-hidden-laptop elementor-section-height-default elementor-section-items-middle wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no\" data-id=\"2d980b8\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;_ha_eqh_enable&quot;:false}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-d772afa\" data-id=\"d772afa\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5597455 elementor-widget__width-inherit elementor-widget-mobile__width-inherit ha-has-bg-overlay elementor-widget elementor-widget-heading\" data-id=\"5597455\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Vol. 26 No. 2 (2023): JITA - APEIRON<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f3e70ee elementor-widget elementor-widget-heading\" data-id=\"f3e70ee\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><strong>Igor Shubinsky, <\/strong>\n<strong> Alexey Ozerov<\/strong><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b0a72e2 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"b0a72e2\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-87a3678 elementor-widget elementor-widget-heading\" data-id=\"87a3678\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-96936f4 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"96936f4\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f04febc elementor-widget__width-initial elementor-widget-mobile__width-inherit elementor-widget elementor-widget-heading\" data-id=\"f04febc\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Original scientific paper<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-389228b elementor-widget__width-initial elementor-widget-mobile__width-inherit elementor-widget elementor-widget-heading\" data-id=\"389228b\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">DOI: <a href=\"http:\/\/localhost\/mytestingsite\/wp-content\/uploads\/2024\/02\/PVTC-Technical-Requirements.pdf\" target=\"_blank\" rel=\"noopener\">https:\/\/doi.org\/10.7251\/JIT2302061S<\/a><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-73b8917 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"73b8917\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/jita-au.com\/wp-content\/uploads\/2024\/03\/10430-Article-Text-23890-1-10-20240103.pdf\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Download Article PDF<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-80faf79 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"80faf79\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8cefffd elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"8cefffd\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers\u2019 expenditures.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0c5e44b elementor-widget elementor-widget-heading\" data-id=\"0c5e44b\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-dee52ab wpr-logo-position-center elementor-widget elementor-widget-wpr-logo\" data-id=\"dee52ab\" data-element_type=\"widget\" data-widget_type=\"wpr-logo.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\n\t\t\t<div class=\"wpr-logo elementor-clearfix\">\n\n\t\t\t\t\t\t\t\t<picture class=\"wpr-logo-image\">\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/jita-au.com\/wp-content\/uploads\/2024\/03\/cc-by-1.png\" alt=\"\">\n\n\t\t\t\t\t\t\t\t\t\t\t<a class=\"wpr-logo-url\" rel=\"home\" aria-label=\"\" href=\"https:\/\/jita-au.com\/\"><\/a>\n\t\t\t\t\t\t\t\t\t<\/picture>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t<a class=\"wpr-logo-url\" rel=\"home\" aria-label=\"\" href=\"https:\/\/jita-au.com\/\"><\/a>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5cb9871 elementor-widget elementor-widget-shortcode\" data-id=\"5cb9871\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\"><div class=\"post-views content-post post-2350 entry-meta load-static\">\r\n\t\t\t\t<span class=\"post-views-icon dashicons dashicons-chart-bar\"><\/span> <span class=\"post-views-label\">Post Views:<\/span> <span class=\"post-views-count\">641<\/span>\r\n\t\t\t<\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Vol. 4 No. 2 (2014): JITA &#8211; APEIRON Lazo Rolji\u0107 Hybrid Methodology of Nonlinear Goal Programming Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT1402068R Download Article PDF Abstract What we demonstrate here is a nonlinear goal-programming (NGP) algorithm based on hybrid connection of the modified simplex method of goal programming, gradient method of feasible directions and method of optimal displacement size finding-called HNGPM. Iterative methodology is given in five steps: (1) linearization the set of nonlinear constraints at particular point, (2) solving the problem of normalized linear goal programming, (3) feasible direction computation, (4) calculating optimal step length displacement, and (5) testing out convergence problem. Our idea was to apply Euler\u2019s theorem for the \u201ctotal\u201d linearization of the nonlinear constraints (in the space) around particular point. According to Euler\u2019s theorem, it is possible to apply this methodology to solve the problems of NGP whether the nonlinear constraint functions are linearly or positively homogeneous. Keywords: Non-linear goal programming, Cobb- Douglas\u2019s production function, Euler\u2019s homogeneous function theorem, feasible directions method. Vol. 26 No. 2 (2023): JITA &#8211; APEIRON Igor Shubinsky, Alexey Ozerov Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT2302061S Download Article PDF Abstract The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers\u2019 expenditures. Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators. Vol. 26 No. 2 (2023): JITA &#8211; APEIRON Igor Shubinsky, Alexey Ozerov Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT2302061S Download Article PDF Abstract The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers\u2019 expenditures. Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.<\/p>\n","protected":false},"author":1,"featured_media":534,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_header_footer","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2350","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Hybrid Methodology of Nonlinear Goal Programming - JITA -Journal of Information Technology and Application<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/jita-au.com\/index.php\/2024\/04\/10\/hybrid-methodology-of-nonlinear-goal-programming\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Hybrid Methodology of Nonlinear Goal Programming - JITA -Journal of Information Technology and Application\" \/>\n<meta property=\"og:description\" content=\"Vol. 4 No. 2 (2014): JITA &#8211; APEIRON Lazo Rolji\u0107 Hybrid Methodology of Nonlinear Goal Programming Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT1402068R Download Article PDF Abstract What we demonstrate here is a nonlinear goal-programming (NGP) algorithm based on hybrid connection of the modified simplex method of goal programming, gradient method of feasible directions and method of optimal displacement size finding-called HNGPM. Iterative methodology is given in five steps: (1) linearization the set of nonlinear constraints at particular point, (2) solving the problem of normalized linear goal programming, (3) feasible direction computation, (4) calculating optimal step length displacement, and (5) testing out convergence problem. Our idea was to apply Euler\u2019s theorem for the \u201ctotal\u201d linearization of the nonlinear constraints (in the space) around particular point. According to Euler\u2019s theorem, it is possible to apply this methodology to solve the problems of NGP whether the nonlinear constraint functions are linearly or positively homogeneous. Keywords: Non-linear goal programming, Cobb- Douglas\u2019s production function, Euler\u2019s homogeneous function theorem, feasible directions method. Vol. 26 No. 2 (2023): JITA &#8211; APEIRON Igor Shubinsky, Alexey Ozerov Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT2302061S Download Article PDF Abstract The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers\u2019 expenditures. Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators. Vol. 26 No. 2 (2023): JITA &#8211; APEIRON Igor Shubinsky, Alexey Ozerov Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT2302061S Download Article PDF Abstract The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers\u2019 expenditures. Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/jita-au.com\/index.php\/2024\/04\/10\/hybrid-methodology-of-nonlinear-goal-programming\/\" \/>\n<meta property=\"og:site_name\" content=\"JITA -Journal of Information Technology and Application\" \/>\n<meta property=\"article:published_time\" content=\"2024-04-10T13:43:53+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-04-29T12:43:40+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/jita-au.com\/wp-content\/uploads\/2024\/03\/cover_issue_949_en_US.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"595\" \/>\n\t<meta property=\"og:image:height\" content=\"793\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/jita-au.com\/index.php\/2024\/04\/10\/hybrid-methodology-of-nonlinear-goal-programming\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/jita-au.com\/index.php\/2024\/04\/10\/hybrid-methodology-of-nonlinear-goal-programming\/\"},\"author\":{\"name\":\"admin\",\"@id\":\"https:\/\/jita-au.com\/#\/schema\/person\/d4becda53cfcbc99c449927eabf3877f\"},\"headline\":\"Hybrid Methodology of Nonlinear Goal Programming\",\"datePublished\":\"2024-04-10T13:43:53+00:00\",\"dateModified\":\"2024-04-29T12:43:40+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/jita-au.com\/index.php\/2024\/04\/10\/hybrid-methodology-of-nonlinear-goal-programming\/\"},\"wordCount\":448,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/jita-au.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/jita-au.com\/index.php\/2024\/04\/10\/hybrid-methodology-of-nonlinear-goal-programming\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/jita-au.com\/wp-content\/uploads\/2024\/03\/cover_issue_949_en_US.jpg\",\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/jita-au.com\/index.php\/2024\/04\/10\/hybrid-methodology-of-nonlinear-goal-programming\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/jita-au.com\/index.php\/2024\/04\/10\/hybrid-methodology-of-nonlinear-goal-programming\/\",\"url\":\"https:\/\/jita-au.com\/index.php\/2024\/04\/10\/hybrid-methodology-of-nonlinear-goal-programming\/\",\"name\":\"Hybrid Methodology of Nonlinear Goal Programming - 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JITA -Journal of Information Technology and Application","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/jita-au.com\/index.php\/2024\/04\/10\/hybrid-methodology-of-nonlinear-goal-programming\/","og_locale":"en_US","og_type":"article","og_title":"Hybrid Methodology of Nonlinear Goal Programming - JITA -Journal of Information Technology and Application","og_description":"Vol. 4 No. 2 (2014): JITA &#8211; APEIRON Lazo Rolji\u0107 Hybrid Methodology of Nonlinear Goal Programming Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT1402068R Download Article PDF Abstract What we demonstrate here is a nonlinear goal-programming (NGP) algorithm based on hybrid connection of the modified simplex method of goal programming, gradient method of feasible directions and method of optimal displacement size finding-called HNGPM. Iterative methodology is given in five steps: (1) linearization the set of nonlinear constraints at particular point, (2) solving the problem of normalized linear goal programming, (3) feasible direction computation, (4) calculating optimal step length displacement, and (5) testing out convergence problem. Our idea was to apply Euler\u2019s theorem for the \u201ctotal\u201d linearization of the nonlinear constraints (in the space) around particular point. According to Euler\u2019s theorem, it is possible to apply this methodology to solve the problems of NGP whether the nonlinear constraint functions are linearly or positively homogeneous. Keywords: Non-linear goal programming, Cobb- Douglas\u2019s production function, Euler\u2019s homogeneous function theorem, feasible directions method. Vol. 26 No. 2 (2023): JITA &#8211; APEIRON Igor Shubinsky, Alexey Ozerov Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT2302061S Download Article PDF Abstract The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers\u2019 expenditures. Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators. Vol. 26 No. 2 (2023): JITA &#8211; APEIRON Igor Shubinsky, Alexey Ozerov Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT2302061S Download Article PDF Abstract The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers\u2019 expenditures. 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