{"ModuleCode":"BDC6111","ModuleTitle":"Foundations of Optimization","Department":"Decision Sciences","ModuleDescription":"This course will cover important topics in optimization theory including linear, network, discrete, convex, conic, stochastic and robust. It will focus on methodology, modeling techniques and mathematical insights. This is a core module for PhD students in the Decision Science department.","ModuleCredit":"4","Workload":"3-0-0-4-3","Prerequisite":"A basic knowledge of linear algebra","AcadYear":"2015/2016","History":[{"Semester":1,"Timetable":[{"ClassNo":"F1","LessonType":"Lecture","WeekText":"Every Week","DayText":"Friday","StartTime":"0900","EndTime":"1200","Venue":"BIZ2-0420"}],"LecturePeriods":["Friday Morning"]}]}