MMPO-001 · June 2023 · English

IGNOU MMPO-001 June 2023 Previous Year Question Paper

OPERATIONS RESEARCH

Structured previous year question paper for MMPO-001, June 2023 session.

Max marks: 100 · Questions: 7

Verified: 11 Sept 2026

MANAGEMENT PROGRAMME (MP)

Term-End Examination

June, 2023

MMPO–001 : OPERATIONS RESEARCH

Time : 3 Hours Maximum Marks : 100

(Weightage : 70%)

Note :

(i) Attempt any five questions.

(ii) All questions carry equal marks. Each

question carries 20 marks.

Q1.What are the essential characteristics of Operations Research ? Discuss the significance and scope of operations research in modern management.

Q2.A firm manufactures two types of products, A and B and sells them at a profit of ` 2 on type A and ` 3 on type B. Each product is processed on two machines, G and H. Type A requires one minute of processing time on G and two minutes on H; type B requires o ne minute on G and one minute on H. Machine G is available for not more than 6 ho urs 40 minutes, while machine H is available for 10 hours during any working day. Formulate the problem as a linear programming problem.

Q3.The assignment cost of assigning an y one operator to any one machine is given below : Operators I II II IV Machine A 10 5 13 15 B 3 9 18 3 C 10 7 3 2 D 5 11 9 7 Find the optimal assignment.

Q4.What is integer programming ? Discuss the importance of integer programming models in supporting decisions.

Q5.What do you mean by the Monte -Carlo simulation method ? Discuss the steps involved in the Monte-Carlo simulation procedure.

Q6.At a certain petrol pump, customers arrive according to a Poisson process with an average time of 5 min utes between arrivals. The service time is exponentially distributed with mean time = 2 minutes. On the basis of this information, find out :

(a) What would be the average queue length ?

(b) What would be the average number of customers in the queuing system ?

Q7.Write short notes on any four of the following :

(i) Applications of Operations Research

(ii) Steps in Stepping–Stone Method

(iii) Big M Method

(iv) Applications of Dynamic Programming

(v) Goal Programming

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