Post Graduate Diploma in Operations Research - II
Syllabus For Second Year of DORM for Finance Stream Candidates
Paper 6: Advance Operations Research I for Finance Stream
6.1 LINEAR PROGRAMMING (LP).
6.1.1 Overview on LP and formulation of realistic LP Problems.
6.1.2 Five Limitations of LP and their resolution.
6.1.3 Review of Simplex method, Symmetric dual, Sensitivity analysis in LP with all less than or equal to constraints.
6.1.4 Dual Simplex method, Unsymmetrical duals and Revised Simplex method.
6.1.5 Sensitivity analysis where constraints are all greater than or equal to or equal to or of mixed type.
6.1.6 Special cases (eg. alternate optima, no feasible solution, unbounded solution and degeneracy) in LP and their resolution.
6.1.7 Application of LP in Portfolio selection, determination of Finance mix, Product mix etc.
6.2 GOAL PROGRAMMING (GP)
6.2.1 What is GP and formulating GP Problems
6.2.2 Solution of GP problem for a maximum of 2/3 valuables by simplex method and interpretation of solution.
6.2.3 Application of GP in Acquisition and merger, Manpower planning etc.
6.3 PARAMETRIC PROGRAMMING (PP).
6.3.1 What is parametric programming?
6.3.2 Tackling simultaneous changes in input. Parameters and simultaneous
changes in resource constraints during sensivity analysis in LP.
6.4 INTEGER LINER PROGAMMING (ILP).
6.4.1 Formulation of ILP problems.
6.4.2 Branch and bound algorithm and cutting Plan algorithm for all integer and mixed ILP.
6.4.3 Egon Bala’s (0-1) algorithm.
6.4.4 Applications of ILP in capital budgeting, determination of number, Size and location of warehouses.
6.5 NETWORK ANALYSIS (NA) including Capacitated Network.
6.5.1 Review of Networking Analysis including crashing of a network and project cost trade off.
6.5.2 Four basic assumption of PERI analysis.
6.5.3 Difference between PERT and CPM.
6.5.4 Resource analysis, resource scheduling and resources smoothing in network analysis-single resource only.
6.5.5 Max flow min cut theorem, undirected arcs, multisource and multilink problem in capacitated network.
6.5.6 Networking for laying commutations electricity distribution, laying pipe lines, reads etc.
Paper 6 : Advance Operation Research I For Marketing Stream
6.1 LINEAR PROGRAMMING (LP)
6.1.1. To 6.1.6: SAME AS FOR FINANCE STREM
6.1.7 Application for LP in media MIk, Product Mix etc.
6.2 INTEGER LINEAR PROGRMING (ILP)
6.2.1 = 6.4.1 of finance stream
6.2.2 = 6.4.2
6.2.3 = 6.4.3
6.2.4 Application of ILP to determine number, size and location of warehouse, developing distribution planning system etc.
6.3 GAME THEORY (GT)
6.3.1 Overview on competitive strategy (Game theory)
6.3.2 Equivalance of GT with LP: solution of (nkm) game problem by matrix method and also through the application of duality in LP
6.3.3 Non Zero sum games-their illustrations
6.3.4 Determination of optimum market share and understanding competitor’s strategies through game theory.
6.4 NETWORK ANALYSIS (NA) including capacitated networks
6.4.1 = 6.5.1 of finance stream
6.4.2 = 6.5.2
6.4.3 = 6.5.3
6.4.4 = 6.5.4
6.4.5 = 6.5.5
6.4.6 Network analysis in new product launching, networking for Communications channels etc.
6.5 SIMULATION AND ITS APPLICATION
6.5.1 Performing simulation by integration variance reducing techniques
6.5.2 Determination of optimum service facility, optimum number of salesmen etc. by using simulation technique.
Paper 6: Advanced Operation Research I for Production Stream
6.1 LINEAR PROGRAMMING (LP)
6.1.1 to 6.1.6 game as for finance stream
6.1.7 Application of LP product mix, Blending, Trim loss etc.
6.2 GOAL PROGRMING (GP)
6.2.1 Same as finance stream
6.2.2 “
6.2.3 Application of GP in multiproduct scheduling, manpower planning etc.
6.3 PARAMETRIC PROGRAMMING (PP)
6.3.1 Same as finance stream
6.3.2 “
6.4 INTEGER LINEAR PROGRAMMING (ILP)
6.4.1 To 6.4.3 same as finance stream
6.4.4 Application of ILP in flexible manufacturing system (FMS)
6.5 NETWORK ANALYSIS (NA) including capacited network
6.5.1 To 6.5.5 same as finance stream
6.5.6 Application of network analysis in scheduling, monitoring and control of projects.
6.5.7 Networking for communication channels, electricity distribution, laying pipe lines, road etc.
Paper 7: Advanced Operations Research II for Production Management
7.1 DEMAND FORECASTING
7.1.1 To 7.1.3 same as marketing stream
7.1.4 Use of the above techniques in demand forecasting for raw materials, men spares etc.
6.1 LINEAR PROGRAMMING (LP)
6.1.1 To 6.1.6 same as for finance steam
6.1.7 Application of LP in salary structuring, vendoring, determining optimum crop rotation etc.
6.2 INTEGER LINEAR PROGRAMMING (I L P)
6.2.1 To 6.2.4 copy form those of finance steam
6.3 GOAL PROGRAMMING
6.3.1 To 6.3.3 copy form those of finance steam
6.4 NETWORK ANALYSES (NA) INCLUDING CAPACITATED NETWORK
6.4.1 = 6.5.1 of finance stream
6.4.2 = 6.5.2 of finance stream
6.4.3 = 6.5.3 of finance stream
6.4.4 = 6.5.4 of finance stream
6.4.5 = 6.5.5 of finance stream
6.4.6 = 6.5.6 of finance stream
6.5 SIMULATION AND ITS APPLICATION
6.5.1 Performing simulation using variance reducing techniques
6.5.1 Determination of optimum service facility by using simulation techniques
6.6 MANPOWER PLANNING
6.6.1 = 6.4.1 of production stream
6.6.2 = 6.4.2 of production stream
Paper 7: Advanced Operation Research II for Finance stream
7.1 SCIENTIFIC INVENTORY MANAGEMENT
7.1.1 Review of inventory management principles plus comparison of periodic Review System (p-system) with two bin or EOQ –ROL System (Q-System)
7.1.2 EOQ for a singal product when shortage is permitted; EOQ for multiproduct when no shortage is permitted.
7.1.3 EOQ under certainty with limitations on capital, and warehouse space, optimal policy curve.
7.1.4 Computation of safety stock and reorder level for number of units short, time out of stock and time weighted and units short.
7.1.5 Model for purchasing insurance spares without and with salvage value.
7.1.6 Control of works in progress and finished goods inventory.
(a) raw material and stores (b) in process inventory
(C) Finished goods inventory and (d) space parts.
7.2 INVESTMENT DECISION
7.2.1 Review of indices to be followed during investment documents.
7.2.2 Dad volume profit (CVP) analysis under uncertainty. When only sales quantity is a random variable as also when sales quantity, price, variable and fixed costs are all considered as random variables.
7.2.3 Hertz and Hiller model for investments under uncertainty.
7.2.4 Application of above principles during any capital investments.
7.3 DECISION TREE (DT) FOR DECISION MAKING
7.3.1 Concept of DT, Collection information and drawing up a DT Roll back concept for its analysis.
7.3.2 Application of DT in investment analysis without and with discounting the money.
7.4 BAYESIAN APPROACH (BA) IN DECISION ANALYSIS
7.4.1 What is Bayesian approach and application of Bayes theorm in decision making.
7.4.2 Prior, Posterior and Pre-Posterior analysis for Bayesian approach in decision making.
7.4.3 Application of Bayesian Analysis in investment decision, and exploratory work.
7.5 Dynamic Programming (DP)
7.5.1 Concept of dynamic Programmes, Principles of optimality Illustrative examples in stage coach problem, optimum routing, allocation of salesmen to territories etc.
7.5.2 Monrovian decision process without and with rewards, Erotic process, Howard’s Policy space technique with Illustrative examples.
7.5.3 Application of DP in Buying/ Selling at varying prices and inventory control of seasonal products.
Paper 7: Advanced Operations Research II for Marketing Stream
7.1 SALES FORECASTING
7.1.1 Review of qualitative forecasting and single exponential smoothing techniques.
7.1.2 Double exponential smoothing, peter winter’s model base series analysis for seasonal using exponential smoothing.
7.1.3 Trigg’s adaptive Response Rate Single Exponential, Smoothing (ARRSES)
7.1.4 Use of the above Techniques in sales forecast and forecasting of space.
7.7.2 SCIENTIFIC INVENTORY MANAGEMENT
7.2.1 = 7.7.1 of finance stream
7.2.2 = 7.7.2
7.2.3 = 7.1.3 of finance stream
7.2.4 = 7.1.4
7.2.5 = 7.1.5
7.2.6 Application of above inventory management techniques in finished goods inventory and spare parts management.
7.3 DECISION TREE (DT) FOR DECISION MAKING
7.3.1 =7.3.1 of finance stream
7.3.2 = Application of D.T. in pricing analysis and competitive bidding.
7.4 BAYESIAN APPROACH (BA) IN DECISION ANALYSIS
7.4.1 = 7.4.1 of FINANCE STREAM
7.4.2 = 7.4.2
7.4.3 = 7.4.3 Application of Bayesian analysis in evaluating efficacy of market research, test marketing etc
7.5 DYNAMIC PROGRAMMING
7.5.1 = Copy 7.5.1 of Finance Stream
7.5.2 = Copy 7.5.2 of Finance Stream
7.5.3 Application of DP for inventory control of Seasonal products, allocation of salesman to territories etc.
7.2 SCIENTIFIC INVENTORY MANAGEMENT
7.2.1 To 2.6 same as marketing stream
7.3 JOB SEQERRING
7.3.1 Assumption and limitations of sequencing in jobs on s m machines :
7.3.2 Working on the following Algorithms for sequencing n jobs on a maximum of 4 machines
(a) Palmer’s (b) Gupta’s (c) Cambel, Dech and Smith (CDS).
(D) Branch and Bound. Advantages of one over the other.
7.3.3 Optimum sequencing of jobs particularly on jobbing tape of industries, Printing of dyeing industry etc.
7.4 MANPOWER PLANNING
7.4.1 Developing transition matrix for an organization
7.4.2 Application of man avian process to determine steady state manpower requirement over the planning horizon.
7.5 WAITING LINE MODELS
7.5.1 Review of queuing parameters and single service queues plus two basic approaches for tacking queuing problems.
7.5.2 Waiting line models of the following tapes M/M/S/ , /M/M/S/N,
M/G/1/, M/E/S/ with illustrative examples.
7.5.3 Finite source queues plus machine Interference problems.
7.2.4 Application of waiting line models to determine optimum number of fitters (for maintenance), setters, number of machine heads (eg. spindles) per operator etc.
7.1 SCIENTIFIC INVENTORY MANAGEMENT
7.1.1 to 7.1.4 Copy form those of finance stream
7.1.5 Application of above inventory management techniques for stores item, water management, cash management , vendoring and sub contracting etc.
7.2 INVESTMENT DECISIONS
7.2.1 Review of indices to be followed during investment decisions.
7.2.2 Hertz and Hiller model for investment under uncertainty.
7.2.3 Application of the above principles in cost benefit analysis, determining optimum replacement period of cars, Computers, Typewriters, Xeroxing machines and other service equipments.
7.3 DECISION TREE (DT) FOR DECISION MAKING
7.3.1 Copy 7.3.1 of finance Stream.
7.3.2 Application of DT in site selection and in investment analysis with discounting.
7.4 BAYESIAN APPROACH (BA) IN DECISION ANALYSIS
7.4.1 and 7.4.2 same as those of finance stream
7.4.3 Application of Bayesian Analysis in exploratory work (eg oil exploration) in assessing effectiveness of training etc.
7.5 DYNAMIC PROGRAMMING (DP)
7.5.1 = 7.5.1 of Finance Stream
7.5.2 = 7.5.2 of Finance Stream
5.5.3 = Application of DP in determining optimum service facility (eg determining optimum number of experts to be put in a research team to maximize reliability subject to finance constraint etc.)
Paper 8 : Use of Computers in O.R.
Role of computers, information systems and database in application of O.R. in large scale systems; evolution of systems through electronic data processing, database processing, Management information systems, decision support systems ; knowledgebase systems; Expert systems .
Functional organization of digital computers elements of personal computers; basic concepts of an operating system such as DOS; Common types of application software.
Basic structure of a program in C Language an in COBOL; basic difference in the types of scientific and business computing; types of files and issues in organization of information in files in c and COBOL.
Evolution of relational database systems; entity-relation diagrams; considerations in design of large databases; role of quety languages elements of dBASE.
Digital System simulation; concepts in design of simulation experiments; tapes o simulation language.
Paper 9: DORM – Second Year Integrated Approach to O.R.
1. Place of O.R. in a business/Service organization. Its role and contribution to the overall management decision making process in an organization
2. O.R. Department’s organizational set up and inter-Disciplinary team approach.
3. Interface/integration of O.R. Department with other line and staff functional Department ; the need for their involvement in O.R. projects; area of Co-operation and conflicts; resolution of conflicts.
4. Basic Principles of strategic management and role of O.R. in their repayment and contribution of O.R. Department in planning. Adoptive running- satisfying optimizing and adopting, through O.R.
