<div class="xblock xblock-public_view xblock-public_view-vertical" data-usage-id="block-v1:MITx+15.053x+3T2016+type@vertical+block@e5a03303cae44c0ca4ea7e0a4eef805f" data-block-type="vertical" data-graded="False" data-course-id="course-v1:MITx+15.053x+3T2016" data-has-score="False" data-request-token="e9396c16852011ef8f53023e4242adeb" data-init="VerticalStudentView" data-runtime-class="LmsRuntime" data-runtime-version="1"> <h2 class="hd hd-2 unit-title">This Course on Open Learning Library</h2> <div class="vert-mod"> <div class="vert vert-0" data-id="block-v1:MITx+15.053x+3T2016+type@html+block@558073f2569a4c79a828807a9a508ae4"> <div class="xblock xblock-public_view xblock-public_view-html xmodule_display xmodule_HtmlBlock" data-usage-id="block-v1:MITx+15.053x+3T2016+type@html+block@558073f2569a4c79a828807a9a508ae4" data-block-type="html" data-graded="False" data-course-id="course-v1:MITx+15.053x+3T2016" data-has-score="False" data-request-token="e9396c16852011ef8f53023e4242adeb" data-init="XBlockToXModuleShim" data-runtime-class="LmsRuntime" data-runtime-version="1"> <script type="json/xblock-args" class="xblock-json-init-args"> {"xmodule-type": "HTMLModule"} </script> <p>In this version of <i>Optimization Methods in Business Analytics</i> on Open Learning Library:</p> <ul> <li>No certificates can be earned on Open Learning Library</li> <li>Runs as ‘self-paced’ and all dates mentioned within are irrelevant</li> <li>Some assessment material may have been removed and grading adjusted accordingly</li> <li>Any discussion forums have been removed</li> <li>All assessments have been set to unlimited attempts</li> <li>Some course content may have been removed </li> </ul> <p></p> </div> </div> </div> </div>

<div class="xblock xblock-public_view xblock-public_view-vertical" data-usage-id="block-v1:MITx+15.053x+3T2016+type@vertical+block@e47b68e86925454f828a76005649ff92" data-block-type="vertical" data-graded="False" data-course-id="course-v1:MITx+15.053x+3T2016" data-has-score="False" data-request-token="e9396c16852011ef8f53023e4242adeb" data-init="VerticalStudentView" data-runtime-class="LmsRuntime" data-runtime-version="1"> <h2 class="hd hd-2 unit-title">Syllabus</h2> <div class="vert-mod"> <div class="vert vert-0" data-id="block-v1:MITx+15.053x+3T2016+type@html+block@e3d68ff8ef114d8d9f3ec6f65b51ab51"> <div class="xblock xblock-public_view xblock-public_view-html xmodule_display xmodule_HtmlBlock" data-usage-id="block-v1:MITx+15.053x+3T2016+type@html+block@e3d68ff8ef114d8d9f3ec6f65b51ab51" data-block-type="html" data-graded="False" data-course-id="course-v1:MITx+15.053x+3T2016" data-has-score="False" data-request-token="e9396c16852011ef8f53023e4242adeb" data-init="XBlockToXModuleShim" data-runtime-class="LmsRuntime" data-runtime-version="1"> <script type="json/xblock-args" class="xblock-json-init-args"> {"xmodule-type": "HTMLModule"} </script> <h2>Course Staff</h2> <ul> <li><b>Lecturer: </b> Prof. James B. Orlin </li> <li><b>Teaching Assistant:</b> Khizar Qureshi</li> </ul> <h2>Grading</h2> <ul> <li><b>Problem sets [6]:</b> 90%. Each problem set is worth 15% of the final grade. </li> <li><b>Lecture exercises (also called "finger exercises"):</b> 10%</li> </ul> </div> </div> <div class="vert vert-1" data-id="block-v1:MITx+15.053x+3T2016+type@html+block@faa9ae89939e4fe1907ce7cb1b0057d3"> <div class="xblock xblock-public_view xblock-public_view-html xmodule_display xmodule_HtmlBlock" data-usage-id="block-v1:MITx+15.053x+3T2016+type@html+block@faa9ae89939e4fe1907ce7cb1b0057d3" data-block-type="html" data-graded="False" data-course-id="course-v1:MITx+15.053x+3T2016" data-has-score="False" data-request-token="e9396c16852011ef8f53023e4242adeb" data-init="XBlockToXModuleShim" data-runtime-class="LmsRuntime" data-runtime-version="1"> <script type="json/xblock-args" class="xblock-json-init-args"> {"xmodule-type": "HTMLModule"} </script> <ul> <li>Week 1.Linear programming</li> <li>Week 2. Geometry of linear programming</li> <li>Week 3. Integer programming I</li> <li>Week 4. Integer programming II</li> <li>Week 5. Sensitivity Analysis</li> <li>Week 6. Nonlinear programming</li> </ul> </div> </div> <div class="vert vert-2" data-id="block-v1:MITx+15.053x+3T2016+type@html+block@c3c979192b9942af9f714e7ba45e53d8"> <div class="xblock xblock-public_view xblock-public_view-html xmodule_display xmodule_HtmlBlock" data-usage-id="block-v1:MITx+15.053x+3T2016+type@html+block@c3c979192b9942af9f714e7ba45e53d8" data-block-type="html" data-graded="False" data-course-id="course-v1:MITx+15.053x+3T2016" data-has-score="False" data-request-token="e9396c16852011ef8f53023e4242adeb" data-init="XBlockToXModuleShim" data-runtime-class="LmsRuntime" data-runtime-version="1"> <script type="json/xblock-args" class="xblock-json-init-args"> {"xmodule-type": "HTMLModule"} </script> <ul> <li>Problem sets account for 90% of the grade in 15.053x. We view them as opportunities for the students to think through the topics of this course and develop mastery in solving problems. required. </li> <li>Problem sets are to be completed individually; however, students may discuss the problems with others in the class. Copying from another students is not permitted. Students may not post any part of a solution as part of discussions. </li> <li>Spreadsheets and Julia code should be individual work. (Programming with Julia is encouraged, but it is optional and does not affect a student's grade.) Students may obtain some help from other students. But students should work out details on their own and never copy from another person’s spreadsheet.</li> <li>The due date for a problem sets are provided. (Typically, a problem set is 7 days after the release of the week's materials.) Late assignments will NOT be accepted. Solutions for problem sets become available immediately after the the problem set is due.</li> </ul> </div> </div> <div class="vert vert-3" data-id="block-v1:MITx+15.053x+3T2016+type@html+block@299ca31769174baca0ce0f59056d7f05"> <div class="xblock xblock-public_view xblock-public_view-html xmodule_display xmodule_HtmlBlock" data-usage-id="block-v1:MITx+15.053x+3T2016+type@html+block@299ca31769174baca0ce0f59056d7f05" data-block-type="html" data-graded="False" data-course-id="course-v1:MITx+15.053x+3T2016" data-has-score="False" data-request-token="e9396c16852011ef8f53023e4242adeb" data-init="XBlockToXModuleShim" data-runtime-class="LmsRuntime" data-runtime-version="1"> <script type="json/xblock-args" class="xblock-json-init-args"> {"xmodule-type": "HTMLModule"} </script> <ul> <li><b>Applied Mathematical Programming</b> by Bradley, Hax, and Magnanti. This book has very broad coverage of optimization models as well as algorithms. This book is available on line at <a class="modal-content" href="http://web.mit.edu/15.053/www/index.html"> http://web.mit.edu/15.053/www/index.html</a>. The book is for reference, and students will not have assigned readings.</li> <li><b>Microsoft Excel</b> will be used frequently within 15.053x. Students can use the Add-in “Excel Solver” or the publicly available software OpenSolver. We strongly encourage students to use OpenSolver rather than Excel Solver. Excel Solver is limited to problems with at most 200 variables, and the solution algorithm is not nearly as fast as that of OpenSolver. OpenSolver has no limit on the size of the problem it will solve. Instructions on how to make the add-ins available and how to use them are included in the folder “Excel Information”. </li> <li><b>JuMP and Julia</b>. As stated on the Julia and JuMP websites, “Julia is a high-level, high performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments.” “JuMP is a modeling language for optimization problems. It lets you translate the mathematical statement of an optimization problem into a form the computer can work with, but is still easy for humans to work with.” We provide instructions on how to download and use the software on the course website. </li> </ul> </div> </div> </div> </div>