Course Details
Subject {L-T-P / C} : ME4237 : Decision Modeling { 3-0-0 / 3}
Subject Nature : Theory
Coordinator : Prof. Saroj Kumar Patel
Syllabus
1. LPP: formulation, graphical, simplex, variations of LPP, big M, degeneracy, alternate optimal solution, Unbounded solution, infeasible solution, duality, dual LPP, dual simplex, sensitivity analysis, use of software
2. Transportation Problem: formulation, as LPP, balanced, Corner methods, least cost method, Vogel’s Approximation method, check for optimality using u-v method, Modified distribution method, variations of transportation problem, Transshipment problem, use of software
3. Assignment Problem: as LPP, as Transportation problem, Hungarian method, use of softwares
4. Network Models: Terminology, Shortest route, minimal spanning tree
5. CPM & PERT: network construction, Fulkerson rule, ET/LT, critical path, floats (TF, FF, IF), Project Scheduling, EST/EFT, LST/LFT, AOA/AON, PERT, network crashing, CPM as LPP, use of software
6. Scheduling: Terms, types, assumptions, performance measures, routing, sequencing, Single processor scheduling: SPT, EDD, Moore, WSPT, FCFS, LCFS Flow shop scheduling (2/n, 3/n, m/n), Johnshon rule Job shop: EDD, SPT, FCFS, FISFS, LSF, LWR Aker
7. Decision Theory: DMUU (pessimitic, optimistic, Hurwicz, Laplace, Regret) DMUC, DMUR (EMV, EOL, Decision tree, AHP)
8. Game Theory: Pure strategies, dominated strategy, mixed strategy (Graphical, oddment, LPP)
9. Queuing Theory: classification, Kendall’s nomenclature, Generalized Poisson queue, steady state probabilities, Little’s formula, Single server infinite/finite queue, Multi server infinite/finite queue,
10. Simulation: classification, random number, pseudo random number, random numbers of different distributions, random number generation
11. Forecasting: types of demands, classification of forecasting, Time series forecasting, Causal forecasting, Judgemental forecasting, forecast error
Course Objectives
- It introduces various quantitative techniques for decision making in the management of industrial organizations. It teaches the skill of formulation of proper models suitable for a given business problem as well as the solution techniques in arriving at a decision.
Course Outcomes
One will be able to take decisions related to various situations in operations management using quantitative techniques.
Essential Reading
- Taha, HA, Operation Research: An Introduction, Pearson India
- Buffa, EW and Sarin, AK, Modern Production/ Operations Management, Wiley India
Supplementary Reading
- Hillier, FS Lieberman, GJ Nag, B Basu, P, Introduction to Operations Research, TMH
- Mohanty, PK and Patel, SK, Operations Research, Scientific
Journal and Conferences
- Operations Reserach
- Management Science