Course Objectives:
Objectives of the course are to provide a formal quantitative approach to problem solving and to give an intuition for managerial situations where a quantitative approach is appropriate. In addition, this course also introduces some widely used quantitative models used for business decision.
Course Contents:
Introduction to Linear Programming models: Aggregate planning; Non-linear models: financial portfolio, Production over-time, work force planning, facility layout, warehouse allocation problem; Network models: shortest path, maximum flow, minimum spanning tree; Multi-criteria decision making approach: Analytical hierarchy process (AHP), Data envelopment analysis (DEA), Goal programming techniques (GP); Waiting line models: Little’s law (D/D/1), Simple queue model (M/M/1), multi-server models (M/M/S), Limited server model; Introduction to theory of constraints (TOC); Introduction to Game theory; Replacement models; Scheduling models: n-jobs/3-machines (modified Johnson’s algorithm), n-jobs/m-machines.