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IOSR Journal of Mathematics (IOSR-JM)
e-ISSN: 2278-5728.Volume 6, Issue 1 (Mar. - Apr. 2013), PP 31-34
www.iosrjournals.org
www.iosrjournals.org 31 | Page
A Study on Transhipment Model for Export of Rubber from
Tripura to Bangladesh
Nabendu Sen and Manish Nandi
Department of Mathematics, Assam University, Silchar-788011, India
Abstract: Production of rubber in Tripura is the second largest after Kerala. But a less quantity is
locally utilized compare to other rubber producing states. A large quantity of rubber is transported to
different parts of the country. But transportation costs at present is not so much favourable for the
firms or agencies due to frequent price hike of petroleum. Bangladesh is the neighbouring country of
Tripura. Bilateral trading now a days is functioning smoothly. Industrialization in rubber sector in
Bangladesh needs a sizable quantity of rubber. For exportation of rubber from Tripura to
Bangladesh, a transhipment model is considered to minimize the transportation costs.
Keywords: Transhipment model, Vogel’s Approximation Method, Optimal Solution etc.
I. Introduction:
Tripura, a beautiful green hilly state, surrounded by natural beauty, eye witness of birth of Bangladesh,
turns dubious when debate for development takes place. Climate of Tripura offers wide range of opportunities
for the cultivation of various food crops, fruits, vegetables and flowers and plantation crops. Rubber plantation
in Tripura has gained its momentum at present. According to survey report by Rubber Board of India, one lakh
hectares land area can be utilized for rubber plantation. At present 58 thousand hectares land area is covered
where rubber plantation is taken place. In Tripura, rubber plantation and rubber related other activities has an
important role for the development of the socio-economic status of the State.
Rubber is the important cash crops of the state. Tripura has been declared the Second Rubber Capital of
India after Kerala. Good about Tripura is that it is located on strategically strong position. On three fronts, it is
surrounded by Bangladesh. On one front it is connected with Assam and Mizoram which is linked with
Myanmar. Tripura‟s strategic location can be exploited through bilateral trade, whether it is with Bangladesh,
China, Myanmar, Nepal or Bhutan. On three sides, Tripura, in the past, had excellent transportation links with
the then East Bengal. Many large towns in Bangladesh are within 150 kilometres of the towns in Tripura.
Border trade with Bangladesh will effectively integrate the Tripura Economy to the rest of India as well as to the
other countries in the Region. In fact, it will make Tripura „Gate Way‟ to the “North East” and will give a great
boast to the state economy. This would open up a vast market for the industrial units specially Rubber Industry
units in Tripura. Facilitating cargo movement by using the land ports between Tripura and Bangladesh will cut
down on transport cost for the producers who sell their product to the main land rubber goods industries.
II. Problem Statement:
Rubber has been identified as one of the thrust area in Tripura. Tripura is the second largest rubber
producer in the country, after Kerala. The total area under rubber plantations in Tripura at present is nearly
58,000 hectares and produced nearly 28,000 tone of natural rubber. But merely 6-7% of total production is
locally utilised. Several agencies working in Tripura export rubber to many states and also many countries.
Neighbouring country Bangladesh is one of major rubber importer from Tripura. On the basis of available data
collected from locally working agencies, a transhipment model is developed. 23 sub-divisions of Tripura are
divided into 4 zones and we consider two land custom stations as buffer for transportation.
We consider Z1, Z2 , Z3 ,Z4 for four zones , A(Akhaura) and B(Srimantapur) for land custom stations as
transit centres and X(Dhaka) , Y(Comilla) as destinations where rubber will be exported. Data collected from
the source is given below:-
A B X Y Supply
Z1 2750 3500 ---- ---- 1000
Z2 2675 2500 ----- ----- 700
Z3 5400 2600 ----- ----- 1200
Z4 7600 9780 ---- ----- 600
A 0 3400 9000 16750
B ---- 0 15650 1600
X ----- ----- 0 7500
Demand 2000 1500
A Study on Transhipment Model for Export of Rubber from Tripura to Bangladesh
www.iosrjournals.org 32 | Page
Transportation costs given in the table is in Rupees per 25 tons. On the Basis of the given data we
construct a transhipment network between sources and destinations.
Figure 1: Transhipment Network between sources and destinations.
III. Model Formulation:
The transhipment model can be converted into a regular transportation model with seven sources (Z1, Z2 ,
Z3 , Z4 ,A, B ,X ) and four destinations (A ,B, X, Y ). The formulated model is
Minimize Z = ∑ ∑ cij xij where i =1,2,.....,7 ; j = 1,2,3,4
Subject to ∑ xij = ai , i = 1,2,.....,7 (Supply constraints ), j = 1,2,3,4
∑ xij = bj , j = 1,2,3,4 (demand constraints ), i = 1,2,....,7
and xij ≥ 0 for all i and j
where xij = number of units of the product in ton to be transported from source i (i = 1,2,...,7) to destination
j ( j = 1,2,3,4)
Cij = cost of units (Rupees per 25 tons )
The amount of supply and demand different at the different nodes are computed :
Supply at a pure supply node (Z1 , Z2 , Z3 , Z4) = Original supply
Demand at a pure demand node (X, Y) = Original demand
Supply at a transhipment node (A, B , X ) = Original supply + Buffer amount
Demand at a transhipment node = Original demand + buffer amount.
In this problem buffer amount =Total supply ( or demand )
100+700+ 1200+600(or 2000+1500)
= 3500 tons.
In this present problem, transportation from certain sources to certain destinations is not possible. We can
handle the problem by assigning very large cost by M.
IV. Solution:
To find out the solution of the present problem, we apply more desirable solution method, Vogel‟s
approximation method.
Vogel‟s Approximation Method (VAM)
A B X Y Supply
Z1 2750
1000
3500 M M 1000
Z2 2675
400
2500
300
M M 700
Z3
5400
2600
1200
M M 1200
Z4 7600
600
9780 M M 600
A Study on Transhipment Model for Export of Rubber from Tripura to Bangladesh
www.iosrjournals.org 33 | Page
A 0
1500
3400
9000
2000
16750 3500
B
M
0
2000
15650
1600
1500
3500
X
M M
0
3500
7500 3500
Demand 3500 3500 5500 1500 14000
Initial basic solution ---
X11 = 1000, X21 = 400, X22 = 300, X32 = 1200, X41 = 600, X51 = 1500, X53 = 2000, X62 = 2000, X64 =1500, X73 =
3500.
Min Cost = Rs.(2750x1000 +2675x400 +2500x300 +2600x1200 + 7600x600 + 0x1500 + 9000x2000 +
0x2000 + 1600x1500 + 0x3500)/25
= Rs.13,02,000/-
Figure 2: Solution of the transhipment model.
V. Optimality Test-MODI Method:
The quantities (ui + vj ) for the unoccupied cells are displayed in the circles.
Optimality test table
A B X Y Supply ui
Z1 2750
1000
2575
3500
M M 1000 u1=2750
Z2 2675
400
2500
300
M M 700 u2=2675
Z3
2775
5400
2600
1200
M M 1200 u3=2775
Z4 7600
600
7425
9780
M M 600 u4=7600
A 0
1500
-175
9000
2000
1425 3500 u5=0
A Study on Transhipment Model for Export of Rubber from Tripura to Bangladesh
www.iosrjournals.org 34 | Page
3400 16750
B
M
0
2000
9175
15650
1600
1500
3500 u6=175
X
M M
0
3500
-7575
7500
3500 u7=-9000
Demand 3500 3500 5500 1500 14000
vj v1=0 v2=-175 v3=9000 v4=1425
We compute ∆ij = cij – (ui + vj ), the cell evaluations, for the unoccupied cells.
925
2625
2355
3575 15325
6475
15075
∆12 = 925, ∆31 = 2625, ∆42 = 2355, ∆52 =3575, ∆54 = 15325, ∆63 = 6475, ∆74= 15075
Since all ∆ij > 0, the solution under test is optimal. Thus the optimal solution is
X11 = 1000, X21 = 400, X22 = 300, X32 = 1200, X41 = 600, X51 = 1500, X53 = 2000, X62 = 2000,
X64 =1500, X73 = 3500.
Min Cost = Rs.(2750x1000 +2675x400 +2500x300 +2600x1200 + 7600x600 + 0x1500 + 9000x2000 + 0x2000
+ 1600x1500 + 0x3500)/25
= Rs.13,02,000/-.
VI. Conclusion:
In this paper, we consider two land custom stations to transport rubber sheet from Tripura to
Bangladesh. The optimal solution obtained in this present investigation is same with initial basic feasible
solution which we obtained by applying Vogel‟s approximation method. This model can be applied also for
more than two transit points. Our motto is to minimize the transport cost. This model is useful in other sectors
also.
References
1 A. Jarzemskis, Assumptions of small scale intermodal transport, Transport 2008; 23(1), 16-20.
2 C. Perng and, Z.P. Ho, Receiving and Shipping Management in a Transhipment Centre, Asian Journal of Management and
Humanity Sciences 2007; 1(4), 514-522.
3 G.B. Dantzig, Linear Programming and Extensions, Princeton, N.J.: Princeton University 1963 .
4 H.A. Taha (). Operation Research: An Introduction, Prentice Hall, 7th
Edition, USA 1996.
5 J. Reeb and, S. Leavengood, Transportation Problem: A special case for Linear Programming Problems, Performance Excellence
in the Wood Products Industry, EM 8779, Oregon State University, USA 2002.
6 K. Yamashita, Y. Karuno And M. Lu, An Inapproximability of Transhipment Problems with Per mutable Transit Vectors,
Journal of the Operations Research Society of Japan 2010; 53(3), 220-234.
7 N. Sen, T. Som And B. Sinha, A study of Transportation Problem for an Essential Item of Southern Part of North Eastern
Region of India as an OR Model and Use of Object Oriented Programming, International Journal of Computer Sciences and
Networking Security 2010; 10(4), 78-86.
8 S. Kikuchi, J. Rhee And D. Teodorvic, Applicability of an Agent based Modeling Concept to Modeling of Transportation
Phenomena, Yugoslav Journal of Operation Research 2002; 12(2), 141-156.
9 T. Imam , G. Elsharawy, M. Gomah and I. Samy, Solving Transportation Problem Using Object-Oriented Model, International
Journal of Computer Science and Network Security 2009; 9(2), 353-361.
10 V. Adlakha and, H. Arsham, Managing Cost Uncertainties in Transportation and Assignment Problems, Journal of Applied
Mathematics and Decision Sciences 1998; 2(1), 65-104.
11 Y.T. Herer, , M. Tzur And, E. Yucesan (). The Multi-location Transshipment Problem, IIE Transactions 2006 ;38, 185-200.

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A Study on Transhipment Model for Export of Rubber from Tripura to Bangladesh

  • 1. IOSR Journal of Mathematics (IOSR-JM) e-ISSN: 2278-5728.Volume 6, Issue 1 (Mar. - Apr. 2013), PP 31-34 www.iosrjournals.org www.iosrjournals.org 31 | Page A Study on Transhipment Model for Export of Rubber from Tripura to Bangladesh Nabendu Sen and Manish Nandi Department of Mathematics, Assam University, Silchar-788011, India Abstract: Production of rubber in Tripura is the second largest after Kerala. But a less quantity is locally utilized compare to other rubber producing states. A large quantity of rubber is transported to different parts of the country. But transportation costs at present is not so much favourable for the firms or agencies due to frequent price hike of petroleum. Bangladesh is the neighbouring country of Tripura. Bilateral trading now a days is functioning smoothly. Industrialization in rubber sector in Bangladesh needs a sizable quantity of rubber. For exportation of rubber from Tripura to Bangladesh, a transhipment model is considered to minimize the transportation costs. Keywords: Transhipment model, Vogel’s Approximation Method, Optimal Solution etc. I. Introduction: Tripura, a beautiful green hilly state, surrounded by natural beauty, eye witness of birth of Bangladesh, turns dubious when debate for development takes place. Climate of Tripura offers wide range of opportunities for the cultivation of various food crops, fruits, vegetables and flowers and plantation crops. Rubber plantation in Tripura has gained its momentum at present. According to survey report by Rubber Board of India, one lakh hectares land area can be utilized for rubber plantation. At present 58 thousand hectares land area is covered where rubber plantation is taken place. In Tripura, rubber plantation and rubber related other activities has an important role for the development of the socio-economic status of the State. Rubber is the important cash crops of the state. Tripura has been declared the Second Rubber Capital of India after Kerala. Good about Tripura is that it is located on strategically strong position. On three fronts, it is surrounded by Bangladesh. On one front it is connected with Assam and Mizoram which is linked with Myanmar. Tripura‟s strategic location can be exploited through bilateral trade, whether it is with Bangladesh, China, Myanmar, Nepal or Bhutan. On three sides, Tripura, in the past, had excellent transportation links with the then East Bengal. Many large towns in Bangladesh are within 150 kilometres of the towns in Tripura. Border trade with Bangladesh will effectively integrate the Tripura Economy to the rest of India as well as to the other countries in the Region. In fact, it will make Tripura „Gate Way‟ to the “North East” and will give a great boast to the state economy. This would open up a vast market for the industrial units specially Rubber Industry units in Tripura. Facilitating cargo movement by using the land ports between Tripura and Bangladesh will cut down on transport cost for the producers who sell their product to the main land rubber goods industries. II. Problem Statement: Rubber has been identified as one of the thrust area in Tripura. Tripura is the second largest rubber producer in the country, after Kerala. The total area under rubber plantations in Tripura at present is nearly 58,000 hectares and produced nearly 28,000 tone of natural rubber. But merely 6-7% of total production is locally utilised. Several agencies working in Tripura export rubber to many states and also many countries. Neighbouring country Bangladesh is one of major rubber importer from Tripura. On the basis of available data collected from locally working agencies, a transhipment model is developed. 23 sub-divisions of Tripura are divided into 4 zones and we consider two land custom stations as buffer for transportation. We consider Z1, Z2 , Z3 ,Z4 for four zones , A(Akhaura) and B(Srimantapur) for land custom stations as transit centres and X(Dhaka) , Y(Comilla) as destinations where rubber will be exported. Data collected from the source is given below:- A B X Y Supply Z1 2750 3500 ---- ---- 1000 Z2 2675 2500 ----- ----- 700 Z3 5400 2600 ----- ----- 1200 Z4 7600 9780 ---- ----- 600 A 0 3400 9000 16750 B ---- 0 15650 1600 X ----- ----- 0 7500 Demand 2000 1500
  • 2. A Study on Transhipment Model for Export of Rubber from Tripura to Bangladesh www.iosrjournals.org 32 | Page Transportation costs given in the table is in Rupees per 25 tons. On the Basis of the given data we construct a transhipment network between sources and destinations. Figure 1: Transhipment Network between sources and destinations. III. Model Formulation: The transhipment model can be converted into a regular transportation model with seven sources (Z1, Z2 , Z3 , Z4 ,A, B ,X ) and four destinations (A ,B, X, Y ). The formulated model is Minimize Z = ∑ ∑ cij xij where i =1,2,.....,7 ; j = 1,2,3,4 Subject to ∑ xij = ai , i = 1,2,.....,7 (Supply constraints ), j = 1,2,3,4 ∑ xij = bj , j = 1,2,3,4 (demand constraints ), i = 1,2,....,7 and xij ≥ 0 for all i and j where xij = number of units of the product in ton to be transported from source i (i = 1,2,...,7) to destination j ( j = 1,2,3,4) Cij = cost of units (Rupees per 25 tons ) The amount of supply and demand different at the different nodes are computed : Supply at a pure supply node (Z1 , Z2 , Z3 , Z4) = Original supply Demand at a pure demand node (X, Y) = Original demand Supply at a transhipment node (A, B , X ) = Original supply + Buffer amount Demand at a transhipment node = Original demand + buffer amount. In this problem buffer amount =Total supply ( or demand ) 100+700+ 1200+600(or 2000+1500) = 3500 tons. In this present problem, transportation from certain sources to certain destinations is not possible. We can handle the problem by assigning very large cost by M. IV. Solution: To find out the solution of the present problem, we apply more desirable solution method, Vogel‟s approximation method. Vogel‟s Approximation Method (VAM) A B X Y Supply Z1 2750 1000 3500 M M 1000 Z2 2675 400 2500 300 M M 700 Z3 5400 2600 1200 M M 1200 Z4 7600 600 9780 M M 600
  • 3. A Study on Transhipment Model for Export of Rubber from Tripura to Bangladesh www.iosrjournals.org 33 | Page A 0 1500 3400 9000 2000 16750 3500 B M 0 2000 15650 1600 1500 3500 X M M 0 3500 7500 3500 Demand 3500 3500 5500 1500 14000 Initial basic solution --- X11 = 1000, X21 = 400, X22 = 300, X32 = 1200, X41 = 600, X51 = 1500, X53 = 2000, X62 = 2000, X64 =1500, X73 = 3500. Min Cost = Rs.(2750x1000 +2675x400 +2500x300 +2600x1200 + 7600x600 + 0x1500 + 9000x2000 + 0x2000 + 1600x1500 + 0x3500)/25 = Rs.13,02,000/- Figure 2: Solution of the transhipment model. V. Optimality Test-MODI Method: The quantities (ui + vj ) for the unoccupied cells are displayed in the circles. Optimality test table A B X Y Supply ui Z1 2750 1000 2575 3500 M M 1000 u1=2750 Z2 2675 400 2500 300 M M 700 u2=2675 Z3 2775 5400 2600 1200 M M 1200 u3=2775 Z4 7600 600 7425 9780 M M 600 u4=7600 A 0 1500 -175 9000 2000 1425 3500 u5=0
  • 4. A Study on Transhipment Model for Export of Rubber from Tripura to Bangladesh www.iosrjournals.org 34 | Page 3400 16750 B M 0 2000 9175 15650 1600 1500 3500 u6=175 X M M 0 3500 -7575 7500 3500 u7=-9000 Demand 3500 3500 5500 1500 14000 vj v1=0 v2=-175 v3=9000 v4=1425 We compute ∆ij = cij – (ui + vj ), the cell evaluations, for the unoccupied cells. 925 2625 2355 3575 15325 6475 15075 ∆12 = 925, ∆31 = 2625, ∆42 = 2355, ∆52 =3575, ∆54 = 15325, ∆63 = 6475, ∆74= 15075 Since all ∆ij > 0, the solution under test is optimal. Thus the optimal solution is X11 = 1000, X21 = 400, X22 = 300, X32 = 1200, X41 = 600, X51 = 1500, X53 = 2000, X62 = 2000, X64 =1500, X73 = 3500. Min Cost = Rs.(2750x1000 +2675x400 +2500x300 +2600x1200 + 7600x600 + 0x1500 + 9000x2000 + 0x2000 + 1600x1500 + 0x3500)/25 = Rs.13,02,000/-. VI. Conclusion: In this paper, we consider two land custom stations to transport rubber sheet from Tripura to Bangladesh. The optimal solution obtained in this present investigation is same with initial basic feasible solution which we obtained by applying Vogel‟s approximation method. This model can be applied also for more than two transit points. Our motto is to minimize the transport cost. This model is useful in other sectors also. References 1 A. Jarzemskis, Assumptions of small scale intermodal transport, Transport 2008; 23(1), 16-20. 2 C. Perng and, Z.P. Ho, Receiving and Shipping Management in a Transhipment Centre, Asian Journal of Management and Humanity Sciences 2007; 1(4), 514-522. 3 G.B. Dantzig, Linear Programming and Extensions, Princeton, N.J.: Princeton University 1963 . 4 H.A. Taha (). Operation Research: An Introduction, Prentice Hall, 7th Edition, USA 1996. 5 J. Reeb and, S. Leavengood, Transportation Problem: A special case for Linear Programming Problems, Performance Excellence in the Wood Products Industry, EM 8779, Oregon State University, USA 2002. 6 K. Yamashita, Y. Karuno And M. Lu, An Inapproximability of Transhipment Problems with Per mutable Transit Vectors, Journal of the Operations Research Society of Japan 2010; 53(3), 220-234. 7 N. Sen, T. Som And B. Sinha, A study of Transportation Problem for an Essential Item of Southern Part of North Eastern Region of India as an OR Model and Use of Object Oriented Programming, International Journal of Computer Sciences and Networking Security 2010; 10(4), 78-86. 8 S. Kikuchi, J. Rhee And D. Teodorvic, Applicability of an Agent based Modeling Concept to Modeling of Transportation Phenomena, Yugoslav Journal of Operation Research 2002; 12(2), 141-156. 9 T. Imam , G. Elsharawy, M. Gomah and I. Samy, Solving Transportation Problem Using Object-Oriented Model, International Journal of Computer Science and Network Security 2009; 9(2), 353-361. 10 V. Adlakha and, H. Arsham, Managing Cost Uncertainties in Transportation and Assignment Problems, Journal of Applied Mathematics and Decision Sciences 1998; 2(1), 65-104. 11 Y.T. Herer, , M. Tzur And, E. Yucesan (). The Multi-location Transshipment Problem, IIE Transactions 2006 ;38, 185-200.