{"id":1697,"date":"2024-07-25T18:37:15","date_gmt":"2024-07-25T15:37:15","guid":{"rendered":"https:\/\/www.iem.ihu.gr\/?post_type=course&p=1697"},"modified":"2025-05-28T20:18:59","modified_gmt":"2025-05-28T17:18:59","slug":"76-04","status":"publish","type":"course","link":"https:\/\/www.iem.ihu.gr\/en\/courses\/76-04\/","title":{"rendered":"Optimization Techniques"},"author":5,"template":"","meta":{"_acf_changed":false},"semester":[65],"course_type":[59],"class_list":["post-1697","course","type-course","status-publish","hentry","semester--1-2-7","course_type-optional"],"acf":{"code":"76.04","semester":65,"level":"1","teaching_activities":{"activity_1":{"description":"Theory","weekly_hrs":3,"ects":4},"activity_2":{"description":"","weekly_hrs":"","ects":""},"activity_3":{"description":"","weekly_hrs":"","ects":""},"activity_4":{"description":"","weekly_hrs":"","ects":""},"activity_5":{"description":"","weekly_hrs":"","ects":""}},"type":59,"language":"\u0395\u03bb\u03bb\u03b7\u03bd\u03b9\u03ba\u03ac","erasmus":"\u038c\u03c7\u03b9","url":"https:\/\/exams-sm.the.ihu.gr\/enrol\/index.php?id=149","prerequisites":"","instructors":[2029],"coordinator":"","content":"Introduction to mathematical programming. Necessary conditions for optimality with and without constraints. Lagrange multipliers, KKT (Karush-Kuhn-Tucker) conditions, optimization algorithms and termination criteria. Linear programming (Simplex method, duality, canonical form, Matlab examples).\r\nNetwork optimization (introduction to network theory, minimum path and maximum flow problems, Matlab examples).\r\nInteger programming (cutting planes method, branch and bound method, dual programming, mixed integer programming, Matlab examples).\r\nConstrained optimization (polynomial approximation, Newton, Marquardt, quasi-Netwon).\r\nNonlinear programming (penalty functions, sequential linear approximation, quadratic programming, Matlab examples)","goals":"This course aims at the essential and comprehensive presentation of the basic and advanced optimization techniques and applications that are necessary for production engineers. It focuses on the ever-increasing need of engineers in industry to reduce production costs that make a modern industry viable in the face of international competition. It explains the possibility of using systematic technical decisions that can help in the efficient design and production of products with significant cost savings. The possibility of using such techniques in a variety of different fields of application and in a wide range of industries is emphasized, and the important role that PCs play in solving large-scale optimization problems and complexity, due to the rapid advancement of technology.\r\nUpon successful completion of the course the student will be able to:\r\n- understand the mathematical background on which the basic and advanced optimization techniques necessary in modern production engineering are based,\r\n- distinguish the key features in a real project or a project case study and formulate a realistic optimization problem\r\n- acquire the necessary skills of using computer tools that can solve various types of optimization problems using a computer\r\n- develop teamwork skills and abilities that allow the combination of optimization methods with modern computer design tools, to improve the creative process of conceptual and detailed design of modern production systems.","skills":"Research, analysis and synthesis of data and information using corresponding technologies, decision making, adaptation to new situations, Promoting free, creative and inductive thinking, independent work, Teamwork.","teaching_methods":"Lectures, Exercises, Online guidance, Projected Presentations, E-mail communication, Online Synchronous and Asynchronous Teaching Platform (moodle).","students_evaluation":"Assessment Language: English \/ Greek\r\nThe final grade of the course is formed by 80% by the grade of the theoretical part, and 20% by the grade of project work.\r\nThe grade of the theoretical part is based on a written final examination.\r\nThe written final examination of the theoretical part may include:\r\nSolving problems of application of the acquired knowledge, Short answer questions etc","bib_textbooks":"Optimization, Algorithms and Applications, Rajesh Kumar Arora\r\nOptimization in Operations Research 2nd Edition, Ronald Rardin\r\nIntroduction to Mathematical Optimization, Matteo Fischetti\r\nLinear and Integer Optimization, Theory and Practice, Third Edition, Gerard Sierksma, Yori Zwols","bib_journals":""},"_links":{"self":[{"href":"https:\/\/www.iem.ihu.gr\/en\/wp-json\/wp\/v2\/course\/1697","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.iem.ihu.gr\/en\/wp-json\/wp\/v2\/course"}],"about":[{"href":"https:\/\/www.iem.ihu.gr\/en\/wp-json\/wp\/v2\/types\/course"}],"author":[{"embeddable":true,"href":"https:\/\/www.iem.ihu.gr\/en\/wp-json\/wp\/v2\/users\/5"}],"version-history":[{"count":8,"href":"https:\/\/www.iem.ihu.gr\/en\/wp-json\/wp\/v2\/course\/1697\/revisions"}],"predecessor-version":[{"id":4218,"href":"https:\/\/www.iem.ihu.gr\/en\/wp-json\/wp\/v2\/course\/1697\/revisions\/4218"}],"acf:post":[{"embeddable":true,"href":"https:\/\/www.iem.ihu.gr\/en\/wp-json\/wp\/v2\/staff\/2029"}],"acf:term":[{"embeddable":true,"taxonomy":"course_type","href":"https:\/\/www.iem.ihu.gr\/en\/wp-json\/wp\/v2\/course_type\/59"},{"embeddable":true,"taxonomy":"semester","href":"https:\/\/www.iem.ihu.gr\/en\/wp-json\/wp\/v2\/semester\/65"}],"wp:attachment":[{"href":"https:\/\/www.iem.ihu.gr\/en\/wp-json\/wp\/v2\/media?parent=1697"}],"wp:term":[{"taxonomy":"semester","embeddable":true,"href":"https:\/\/www.iem.ihu.gr\/en\/wp-json\/wp\/v2\/semester?post=1697"},{"taxonomy":"course_type","embeddable":true,"href":"https:\/\/www.iem.ihu.gr\/en\/wp-json\/wp\/v2\/course_type?post=1697"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}