Add the following two new constraints to problem No. 3.41 and find the optimal solution.
Minimize Z = 10a + 6b + 2c s.t –1a + 1b + 1c ≥ 1
3a + 1b – 1c ≥ 2 New constraints are:
4a + 2b + 3c ≤ 5 8a – 1b + 1c ≥ 5
The simplex format of new constraints is:
4a + 2b + 3c + 1S3 = 5 8a – 1b + 1c – 1S4 = 4
Earlier values of a = 1/4 and b = 5/4 and z = 0
4 × ¼ + 2 × 5/4 + 3 × 0 + 1S3 = 5, gives S3 = 3/2, which is feasible.
8 × ¼ – 5/4 × 1+ 0 – S4 = 4 gives S4 = –13/4 is not feasible. Hence the earlier basic solution is infeasible.
We have seen that the first additional constraint has not influenced the solution and only second additional constraint will influence the solution, by introducing both the constraints in optimal table we get:
Table: I.
Problem Profit Cj – 16 – 6 – 2 0 0 0 0 Replace–
variable Rs. Capacity units a b c S1 S2 S3 S4 ment ratio
b –6 5/4 0 1 ½ –3/4 –1/4 0 0 Row 1
a –16 1/4 1 0 –1/2 1/4 –1/4 0 0 Row 2
S3 0 5 4 2 3 0 0 1 0 Row 3
S4 0 –4 –8 1 –1 0 0 0 1 Row 4
Net evaluation
Multiply row 1 by 2 and subtract it from row 3.
Subtract row 1 from row 4.
Multiply row 2 by 4 and subtract from row 3.
Multiply row 2 by 8 and add it to row 4
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132 Operations Research
Table II.
Problem Profit Cj – 10 – 6 – 2 0 0 0 0 Replace–
variable Rs. Capacity units a b c S1 S2 S3 S4 ment ratio
b –6 5/4 0 1 1/2 –3/4 –1/4 0 0
a –10 1/4 1 0 –1/2 1/4 –1/4 0 0
S3 0 3/2 0 0 4 1/2 3/2 1 0
S4 0 –13/4 0 0 –11/2 11/4 –7/4 0 1
Net evaluation 0 0 –4 –2 –4 0 0
Quotient 8/11 16/7
As S4 = – 13/4, the basic solution is not feasible. As net evaluation row elements are either negative or zeros the solution is optimal. Students can see that by using dual simplex method, variable
‘c’ will enter the solution and S4 will leave the solution.
FLOW CHART FOR SIMPLEX METHOD
Linear Programming Models : Solution by Simplex Method 133133133133133
QUESTIONS
1. (a) “Operations Research is a bunch of Mathematical Techniques” Comment.
(b) Explain the steps involved in the solution of an Operations Research problem.
(c) Give a brief account of various types of Operations Research models and indicate their application to Production – inventory – distribution system.
2. A company makes four products, v, x, y and z which flow through four departments–
drilling, milling and turning and assembly. The variable time per unit of various products are given below in hours.
Products Drilling Milling Turning Assembly
v 3 0 3 4
x 7 2 4 6
y 4 4 0 5
z 0 6 5 3
The unit contributions of the four products and hours of availability in the four departments are as under:
Product Contribution in Rs. Department Hours available.
v 9 Drilling 70
x 18 Milling 80
y 14 Turning 90
z 11 Assembly 100
(a) Formulate a Linear Programme for Maximizing the Contribution.
(b) Give first two iterations of the solution by Simplex method.
3. Metal fabricators limited manufactures 3 plates in different sizes, A, B, and C through Casting, Grinding and Polishing processes for which processing time in minutes per unit are given below:
Processing time/unit in minutes.
Sizes Casting Grinding Polishing
A 5 5 10
B 8 7 12
C 10 12 16
Available 16 2 4 32
Hours per Day.
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134 Operations Research
If the contribution margins are Rs.1/–, 2/– and 3/– for A, B and C respectively, find contribution maximizing product mix.
4. A manufacturer can produce three different products A, B, and C during a given time period. Each of these products requires four different manufacturing operations: Grinding, Turning, Assembly and Testing. The manufacturing requirements in hours per unit of the product are given below for A, B, and C:
A B C
Grinding 1 2 1
Turning 3 1 4
Assembly 6 3 4
Testing 5 4 6
The available capacities of these operations in hours for the given time period are as follows:
Grinding 30 hours, Turning: 60 hours, Assembly: 200 hours and Testing: 200 hours.
The contribution of overheads and profit is Rs.4/– for each unit of A, Rs.6/– for each unit of B and Rs.5/– for each unit of C. The firm can sell all that it produces. Determine the optimum amount of A, B, and C to produce during the given time period for maximizing the returns.
5. (a) Briefly trace the major developments in Operations Research since World War II.
(b) Enumerate and explain the steps involved in building up various types of mathematical models for decision making in business and industry.
(c) State and explain the important assumptions in formulating a Linear Programming Model.
6. An oil refinery wishes its product to have at least minimum amount of 3 components: 10%
of A, 20% of B and 12% of C. It has available three different grades of crude oil: x, y, and z.
Grade x contains: 15% of A, 10% of B and 9% of C and costs Rs. 200/– per barrel.
Grade y contains: 18% of A, 25% of B and 3% of C and costs Rs. 250/– per barrel.
Grade z contains 10% of A, 15% of B and 30% of C and costs Rs. 180/– per barrel.
Formulate the linear programming for least cost mix and obtain the initial feasible solution.
7. (a) Define Operations Research.
(b) List the basic steps involved in an Operations Research study.
(c) List the areas in which Operations Research Techniques can be employed.
(d) Give two examples to show how Work Study and Operations Research are complementary to each other.
8. You wish to export three products A, B, and C. The amount available is Rs. 4,00,000/–.
Product A costs Rs. 8000/– per unit and occupies after packing 30 cubic meters. Product B costs Rs. 13,000/– per unit and occupies after packing 60 cubic meters and product C costs Rs. 15,000/–per unit and occupies 60 cubic meters after packing. The profit per unit of A is Rs. 1000/–, of B is Rs. 1500/– and of C is Rs. 2000/–.
The shipping company can accept a maximum of 30 packages and has storage space of 1500 cubic meters. How many of each product should be bought and shipped to maximize profit? The export potential for each product is unlimited. Show that this problem has two
Linear Programming Models : Solution by Simplex Method 135135135135135 basic optimum solutions and find them. Which of the two solutions do you prefer? Give reasons.
9. A fashion company manufactures four models of shirts. Each shirt is first cut on cutting process in the trimming shop and next sent to the finishing shop where it is stitched, button holed and packed. The number of man–hours of labour required in each shop per hundred shirts is as follows:
Shop Shirt A Shirt B Shirt C Shirt D
Trimming shop 1 1 3 40
Finishing shop 4 9 7 10
Because of limitations in capacity of the plant, no more than 400 man–hours of capacity is expected in Trimming shop and 6000 man – hours in the Finishing shop in the next six months. The contribution from sales for each shirt is as given below: Shirt. A: Rs. 12 /– per shirt, Shirt B: Rs.20 per shirt, Shirt C: Rs. 18/– per shirt and Shirt D: Rs. 40/– per shirt.
Assuming that there is no shortage of raw material and market, determine the optimal product mix.
10. A company is interested in manufacturing of two products A and B. A single unit of Product A requires 2.4 minutes of punch press time and 5 minutes of assembly time. The profit for product A is Rs. 6/– per unit. A single unit of product B requires 3 minutes of punch press time and 2.5 minutes of welding time. The profit per unit of product B is Rs. 7/–. The capacity of punch press department available for these products is 1,200 minutes per week.
The welding department has idle capacity of 600 minutes per week; the assembly department can supply 1500 minutes of capacity per week. Determine the quantity of product A and the quantity of product B to be produced to that the total profit will be maximized.
11. A manufacturing firm has discontinued production of a certain unprofitable product line.
This created considerable excess production capacity. Management is considering devote this excess capacity to one or more of three products X. Y and Z. The available capacity on the machines, which might limit output, is given below:
Machine type Available time in machine hours per week.
Milling machine 200
Lathe 100
Grinder 50
The number of machine hours required for each unit of the respective product is as follows.
Productivity (in machine hours per unit)
Product X Product Y Product Z
Milling machine. 8 2 3
Lathe 4 3 0
Grinder 2 0 1
Machine type.
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136 Operations Research
The sales department indicates that the sales potential for products X and Y exceeds the maximum production rate and that of sales potential for product Z is 20 units per week. The unit profit would be Rs. 20/–, Rs.6/– and Rs.8/– respectively for products X, Y and Z.
Formulate a linear programming model and determine how much of each product the firm should produce in order to maximize profit.
12. A jobbing firm has two workshops and the centralized planning department is faced with the problem of allocating the two sets of machines, in the workshops, to meet the sales demand.
The sales department has committed to supply 80 units of product and 100 units of product Q and can sell any amount of product R. Product Q requires special selling force and hence sales department does not want to increase the sale of this product beyond the commitment.
Cost and selling price details as well as the machine availability details are given in the following tables:
Product Sellig price Raw material Labour cost Labour costs Rs. per unit Cost in Rs. per unit In Rs. per unit In Rs. per unit.
Work shop I Work shop II
P 25 5 12 14
Q 32 8 17 19
R 35 10 23 24
Hours per unit Available hours.
Workshop I Work shop II Workshop I Workshop II.
P Q R P Q R
I 2 1 3 2 1.5 3 250 300
II 1 2 3 1.5 3 3.5 150 175
(a) What is the contribution in Rs. per unit for each of the products when made in workshop II and I?
(b) Formulate a linear programming model.
(c) Write the first simplex tableau (Need not solve for optimality).
13. A manufacturer manufactures three products P, Q and R, using three resources A, B and C.
The following table gives the amount of resources required per unit of each product, the availability of resource during a production period and the profit contribution per unit of each product.
(a) The object is to find what product–mix gives maximum profit. Formulate the mathematical model of the problem and write down the initial table.
(b) In the final solution it is found that resources A and C are completely consumed, a certain amount of B is left unutilized and that no R is produced. Find how much of X and Y are to be produced and that the amount of B left unutilized and the total profits.
Machine
Linear Programming Models : Solution by Simplex Method 137137137137137
(c) Write the dual of the problem and give the answers of dual from primal solution.
Products.
Resources P Q R Availability in units
A 3 2 7 1000
B 3 5 6 2500
C 2 4 2 1600
Profit per Unit in Rs. 8 9 10
14. The mathematical model of a linear programming problem, after introducing the slack variables is:
Maximize Z = 50a + 60b + 120c + 0S1 + 0S2 s.t.
2a + 4b + 6c + S1 = 160
3a + 2b + 4c + S2 = 120 and a, b, c, S1 and S2 all ≥ 0.
In solving the problem by using simplex method the last but one table obtained is given below:
5 0 6 0 120 0 0 Capacity
a b c S1 S2
1/3 2/3 1 1/6 0 80/3
5/3 –2/3 0 –2/3 1 40/3
(a) Complete the above table.
(b) Complete the solution y one more iteration and obtain the values of A, B, and C and the optimal profit Z.
(c) Write the dual of the above problem.
(d) Give the solution of the dual problem by using the entries obtained in the final table of the primal problem.
(e) Formulate the statement of problem from the data available.
15. The India Fertilizer company manufactures 2 brands of fertilizers, Sulpha–X and Super–
Nitro. The Sulpher, Nitrate and Potash contents (in percentages) of these brands are 10–5–
10 and 5–10–10 respectively. The rest of the content is an inert matter, which is available in abundance. The company has made available, during a given period, 1050 tons of Sulpher, 1500 tons of Nitrates, and 2000 tons of Potash respectively. The company can make a profit of Rs. 200/– per tone on Sulpha – X and Rs. 300/– per ton of Super– Nitro. If the object is to maximise the total profit how much of each brand should be procured during the given period?
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138 Operations Research
(a) Formulate the above problem as a linear programming problem and carry out the first iteration.
(b) Write the dual of the above problem.
16. Solve:
Minimize S = 1a – 3b + 2c S.t 3a – 1b + 3c ≤ 7
–2a + 4b + 0c ≤ 12
–4a + 3b + 8c ≤ 10 and a, b, c, all ≥ 0.
17. Solve:
Maximize Z = 3x + 2y + 5z s.t.
1x + 2y + 1z ≤ 430 3x + 0y + 2z ≤ 460
1x + 4y + 0z ≤ 420 and x, y, z all ≥ 0.
18. A manufacturer of three products tries to follow a polity producing those, which contribute most to fixed costs and profit. However, there is also a policy of recognizing certain minimum sales requirements currently, these are: Product X = 20 units per week, Product Y 30 units per week, and Product Z 60 units per week. There are three producing departments. The time consumed by products in hour per unit in each department and the total time available for each week in each department are as follows:
Time required per unit in hours.
Departments X Y Z Total Hours Available
1 0.25 0.20 0.15 420
2 0.30 0.40 0.50 1048
3 0.25 0.30 0.25 529
The contribution per unit of product X, Y, and Z is Rs. 10.50, RS. 9.00 and Rs. 8.00 respectively. The company has scheduled 20 units X, 30 units of Y and 60 units of Z for production in the following week, you are required to state:
(a) Whether the present schedule is an optimum from a profit point of view and if it is not, what it should be?
(b) The recommendations that should be made to the firm about their production facilities (from the answer of (a) above).
19. Minimize Z = 1a – 2b – 3c s.t.
–2a + 1b + 3c = 2
2a + 3b + 4c = 1 and all a, b, and c are ≥ 0.
(b) Write the dual of the above and give the answer of dual from the answer of the primal.
Linear Programming Models : Solution by Simplex Method 139139139139139 20. Minimize Z = 2x + 9y + 1z s.t
1x +4y + 2z ≥ 5
3x + 1y + 2z ≥ 4 and x, y, z all are ≥ 0, Solve for optimal solution.
21. Minimize Z = 3a + 2b + 1c s.t.
2a + 5b + 1c = 12
3a + 4b + 0c = 11 and a is unrestricted and b and c are ≥ 0, solve for optimal values of a, b and c.
22. Max Z = 22x + 30y + 25z s.t 2x + 2y + 0z ≤ 100
2x + 1y + 1z ≤ 100
1x + 2y + 2z ≤ 100 and x, y, z all ≥ 0 Find the optimal solution.
23. Obtain the dual of the following linear programming problem.
Maximize Z = 2x + 5y + 6z s.t.
5x + 6y – 1z ≤ 3 –1x + 1y + 3z ≥ 4 7x – 2y – 1x ≤ 10 1x – 2y + 5z ≥ 3
4x + 7y –2z = 2 and x, y, z all ≥ 0
24. Use dual simplex method for solving the given problem.
Maximize Z = 2a – 2b – 4c s.t 2a + 3b + 5c ≥ 2
3a + 1y + 7z ≤ 3
1a + 4b + 6c ≤ 5 and a, b, c all ≥ 0
25. Find the optimum solution to the problem given:
Maximize Z = 15x + 45y s.t.
1x + 16y ≤ 240 5x + 2y ≤ 162
0x + 1y ≤ 50 and both x and y ≥ 0
If Zmax and c2 is kept constant at 45, find how much c1 can be changed without affecting the optimal solution.
26. Maximize Z = 3a + 5b + 4c s.t.
2a + 3b + 0c ≤ 8 0a + 2b + 5c ≤ 10
3a + 2b + 4c < 15 and a, b, c all ≥ 0
Find the optimal solution and find the range over which resource No.2 (i.e., b2) can be changed maintaining the feasibility of the solution.
27. Define and explain the significance of Slack variable, Surplus variable, Artificial variable in linear programming resource allocation model.
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140 Operations Research
28. Explain how a linear programming problem can be solved by graphical method and give limitations of graphical method.
29. Explain the procedure followed in simplex method of solving linear programming problem.
30. Explain the terms:
(a) Shadow price, (b) Opportunity cost, (c) Key column, (d) Key row
(e) Key number and (f) Limiting ratio.
4.1. INTRODUCTION
In operations Research Linear programming is one of the model in mathematical programming, which is very broad and vast. Mathematical programming includes many more optimization models known as Non - linear Programming, Stochastic programming, Integer Programming and Dynamic Programming - each one of them is an efficient optimization technique to solve the problem with a specific structure, which depends on the assumptions made in formulating the model. We can remember that the general linear programming model is based on the assumptions:
(a) Certainty
The resources available and the requirement of resources by competing candidates, the profit coefficients of each variable are assumed to remain unchanged and they are certain in nature.
(b) Linearity
The objective function and structural constraints are assumed to be linear.
(c) Divisibility
All variables are assumed to be continuous; hence they can assume integer or fractional values.
(d) Single stage
The model is static and constrained to one decision only. And planning period is assumed to be fixed.
(e) Non-negativity
A non-negativity constraint exists in the problem, so that the values of all variables are to be ≥ 0, i.e. the lower limit is zero and the upper limit may be any positive number.
(f) Fixed technology
Production requirements are assumed to be fixed during the planning period.