Decision Modeling is an important component of Operations Research with optimization at its core. Decision problems are in the focus of academicians and practitioners the world over and are solved everywhere from manufacturing to service organizations, airlines, government and consulting houses. The present course is taught from a practitioner’s angle. Theory is introduced to complement the practice and for ease of understanding. The course is mainly meant for Engineering students. The management students will also benefit from the course. In this course on decision modeling, first 2 weeks are devoted to dynamic programming. Dynamic programming helps to solve complex decision problems with the help of Bellman’s principal of optimality. Next 2 weeks cover integer programming which is again very important in decision making context. Branch and bound, cutting plane, and branch and cut methods are discussed in this section. Next 2 weeks cover nonlinear programming which includes constrained and unconstrained optimization, Karush-Kuhn-Tucker conditions and other topics. The final 2 weeks are devoted to metaheuristics that include genetic algorithm, simulated annealing, tabu search and other algorithms.