Revista Mexicana de Ciencias Agrícolas   volume 10  number 3   April 01 - May 15, 2019

DOI: https://doi.org/10.29312/remexca.v10i3.1230

Article

Transportation model for the distribution of cocoa in Mexico

Samuel Rivera López1

Maricruz Gutiérrez Hernández2

Francisco Pérez Soto3

1Chapingo Autonomous University. Avenida Úrsulo Galván, 7B, Colonia Salitrería, Texcoco de Mora, State of Mexico, Mexico. CP. 56150. Tel. 01 (275) 1095016. (sriveral-comercio@hotmail.com). 2Chapingo Autonomous University. Florida Street 67, Colonia El Arenal, Zacualtipán de Ángeles, Hidalgo, Mexico. CP. 43200. Tel. 01(556) 1724351. (maricruzgutt@hotmail.com). 3Division of Economic-Administrative Sciences-Chapingo Autonomous University. Mexico-Texcoco Highway km 38.5, Chapingo, Mexico. CP. 56230.

§Corresponding author: perezsotofco@gmail.com.

Abstract

Cocoa is a product originating in Mexico whose production does not meet domestic demand, so there is a need to import much of what the Mexican market consumes, therefore, it is of great importance to distribute optimally the quantities produced internally with the purpose of minimizing the transportation costs of the grain. The objective of the research was to formulate a transport model that optimizes the distribution of cocoa in Mexico, minimizing the cost of transportation, both for a closed economy and for an open economy. Linear programming was used to solve the transport problem, since it allows determining the optimal way to transfer goods, minimizing total distribution costs. The main results show that the national apparent consumption, in 2015, was 51 394.13 t, the apparent per capita consumption of cocoa in the country was 0.43 kg. The states that can see totally satisfied their demand for cocoa, only with the surplus of state production of Tabasco and Chiapas, are: Guerrero, Oaxaca, Querétaro, Quintana Roo, Tamaulipas, Veracruz, Campeche, Mexico City, Hidalgo, State of Mexico, Morelos, Puebla, Tlaxcala and Yucatán, while Michoacán can obtain 14 of the 65 trucks it demands. The above, leads to a minimization of transportation costs, this being $9 500 068.00. In order to meet the national demand for cocoa, two ports of entry for this crop were considered and the minimum transportation cost was $18 123 640.00.

Keywords: closed economy, import logistics, linear programming, open economy.

Reception date: February 2019

Acceptance date: April 2019

Introduction

Cocoa (Theobroma cacao) is a culture native to Mexico, of cultural importance for the country, so there is a general statement of protection of the appellation of origin of the ‘Cacao Grijalva’ that protects green or roasted/ground cocoa of the species in mention that takes place in the Grijalva Region of Tabasco, this one is integrated by three productive subregions: Chontalpa, Mountain range and Center and they group 11 municipalities of Tabasco (DOF, 2016). The tropical region of America presents the optimal conditions for the cultivation of cocoa, so in these areas it has been cultivated for about three thousand years by the Olmec culture; however, the Maya are attributed the spreading of the grain when they use it, even as a currency in their barter system (Nisao, 2007).

The peoples of Mesoamerica gave a great deal of sentimental value to cocoa since they considered it a gift from the gods; in fact, Theobroma in Greek means ‘food of the gods’, the fruit symbolized the human heart and chocolate contained blood; currently, cocoa and its derivatives have a prominent role in international markets, especially in agro-industry (Salas and Hernández, 2015). In 2017, according to the Agri-Food and Fisheries Information Service (SIAP), in Mexico, 27 287.25 t of cocoa were produced, the producing states of this grain were: Tabasco with 17 430 21 t harvested, Chiapas with 9 611 63 t and Guerrero with 245 41 t (SIAP, 2018).

It should be noted that the production of cocoa in Mexico is in the hands of 37 thousand producers, approximately, Tabasco includes 68% of these, Chiapas has 31% of them and Guerrero has about 1% remaining (Orozco, 2018).

“The 80% of world production is concentrated in cocoas: outsiders or ordinary, trinitario and creole and Mexico has all three types and promotes the increase of creole cocoas, since it is the country of origin” (Jaramillo, 2017). However, in terms of cocoa production, “the socioeconomic and parasitological factors that limit production in a precise and precise manner have not been identified in Mexico and everything points to the fact that diseases contribute significantly to the disappearance of this important crop” (Hernández et al., 2015), given that the import of this grain is essential to meet domestic demand. In 2017, 41 321 97 t of cocoa were imported from around the world, the main suppliers were: Ecuador with 27 012 64 t, Ivory Coast with 9 076 7 t, Colombia with 3 022 33 t, Peru with 1 350 98 t and Republic Dominican Republic with 840.63 t (SIAVI, 2018).

The objective of the work was to state a transport model that optimizes the distribution of cocoa in Mexico, minimizing the cost of transportation. The hypothesis was that the national production of cocoa could only supply the demand of the southern states of the country, given the geographical proximity they have with respect to the producing states, while the states of the center-north of the country would depend on the imports of cocoa to see your demand satisfied. Imports have been gaining more weight in the consumption of national cocoa, mainly due to the growing demand of large chocolate companies that fail to meet their requirements in the domestic market due to the scarce national production of grain (Andrade, 2017). Therefore, in a complementary manner, a minimum cost transport model for an open economy was developed.

Materials and methods

Within the applications of linear programming highlights the problem of transport whose purpose is to determine the optimal way to move goods, since “transportation generally represents the single most important element in logistics costs for most companies. It has been observed that cargo movement absorbs between one and two thirds of total logistics costs” (Quintero et al., 2016). It should be noted that “the general problem of transport -refers literally or figuratively- to the distribution of any goods from any group of supply centers, called origins, to any group of reception centers, called destinations, in such a way that the total distribution costs are minimized” (Hillier and Lieberman, 2010).

In general, the origin Oi ( has Xi units to offer and the destination Dj  has a demand of Xj units. In the case of Mexican cocoa, there are two origins in a closed economy and 30 destinations. In some applications, the quantities of supply or resources and of demand have integer values, and when working with the model it will be required that the quantities distributed take integer values; it should be noted that the entire programming is a problem of linear programming in which it is required that some or all of the variables adopt non-negative integer values (Winston, 2005).

The property of whole solutions establishes that for transport problems in which Xi and Xj have an integer value, all the basic variables (assignments), in all the feasible basic solution (including the optimal one), also have integer values. For its part, ownership of feasible solutions establishes that a necessary and sufficient condition for a transportation problem to have feasible solutions is that (Hillier and Lieberman, 2010).

This property can be verified by observing that the restrictions require that.

The condition that the total resources must equal the total demand requires that the system be balanced, if the problem has some physical meaning and this condition is not met, it would imply that , or , represent a dimension and not an exact requirement. In this case, an imaginary or fictitious origin or destination can be introduced to capture the slack, in order to convert the inequalities into equalities and satisfy the feasibility condition (Hillier and Lieberman, 2010). In this sense, given that cocoa production in Mexico does not satisfy domestic demand, it is necessary to import this product, so, for the open economy model, two fictitious origins were added, Jalisco and Yucatán.

To determine which states of Mexico are deficit or surplus in the consumption of cocoa, the apparent national consumption was calculated, the result was divided among the national population to obtain the apparent consumption per capita. The data obtained was multiplied by the population of each state and its consumption was estimated. The production minus the demand for this grain determined whether the state is a supplying or demanding cocoa. The formulas used were the following (Miranda, 2005).

Apparent national consumption= production + import - export

Where: national apparent consumption= is the quantity demanded of cocoa in tons by the Mexican market; production= it refers to the amount of cocoa harvested in Mexico in tons, the data was consulted in the Agri-Food and Fisheries Information Service (SIAP), the year of study was 2015; import= it is the imported quantity of cocoa expressed in tons, tariff item 18010001 “Cocoa beans, whole or split, raw or roasted” was used. The data was consulted in the Internet Tariff Information System (SIAVI) for the year 2015; export= it is the quantity exported of cocoa expressed in tons; tariff item 18010001 “cocoa beans, whole or split, raw or roasted” was used. The data was consulted in the SIAVI for the year 2015.

Where: apparent consumption per capita= it is the quantity demanded of cocoa for each person in Mexico; National population= express the number of inhabitants in Mexico in 2015, the data was consulted in the National Institute of Statistics and Geography (INEGI).

State consumption = apparent consumption per capita *state population

State population= is the number of inhabitants in each of the states of Mexico in 2015, the data was consulted in the INEGI.

The transportation costs were estimated from the trial version of the GlobalMap Software “roads of road transportation of Mexico 2018”. They were calculated for a type T3-C2 transport that, according to NOM-012-SCT-2-2017, has a capacity of 30 t (DOF, 2017). Therefore, the deficit or surplus quantities used in the model are presented in truck units.

The origin (Oi) states were those whose production was greater with respect to their consumption; that is, those that had a surplus, while the destination states (Dj) were those that presented a deficit. Origins were taken as the larger cities near the area of production of each state, while destinations for state capitals were used, considering that the bulk of economic activity, mostly concentrated in them.

The variable X11 corresponds to the origin ‘Chiapas’ and destination ‘Aguascalientes’, the variable X12 belongs to the origin ‘Chiapas’ and destination ‘Baja California’, ..., the variable X130 belongs to the origin ‘Chiapas’ and destination ‘Zacatecas’. For its part, the variable representing the origin ‘Tabasco’ and destination ‘Aguascalientes’ is X21, ..., and the origin ‘Tabasco’ and destination Zacatecas’ is X230.

For the open economy, two fictitious origins were used: Jalisco and Yucatán, initiating their variables with X3 and X4, respectively.

Model for a closed economy

Objective function

MIN 22282X11+49509X12+51168X13+11251X14+34585X15+15348X16+24842X17+25499X18+26931X19+20120X110+18263X111+15362X112+22842X113+16381X114+19493X115+15934X116+26495X117+25739X118+6757X119+13456X120+18042X121+10104X122+20197X123+33333X124+41904X125+18344X126+13872X127+11987X128+12903X129+23480X130+17745X21+44647X22+46554X23+4691X24+30061X25+10486X26+19980X27+20965X28+22068X29+15586X210+13726X211+10502X212+18303X213+11518X214+14923X215+11071X216+21633X217+20880X218+6648X219+8591X220+13500X221+5783X222+15660X223+28796X224+37046X225+13809X226+9010X227+7129X228+6346X229+18946X230.

Offer restrictions

X11+X12+X13+X14+X15+X16+X17+X18+X19+X110+X111+X112+X113+X114+X115+X116+X117+X118+X119+X120+X121+X122+X123+X124+X125+X126+X127+X128+X129+X130=270

X21+X22+X23+X24+X25+X26+X27+X28+X29+X210+X211+X212+X213+X214+X215+X216+X217+X218+X219+X220+X221+X222+X223+X224+X225+X226+X227+X228+X229+X230=578.

Demand constraints

X11+X21<=18

X12+X22<=47

X13+X23<=10

X14+X24<=12

X15+X25<=10

X16+X26<=74

X17+X27<=50

X18+X28<=128

X19+X29<=25

X110+X210<=83

X111+X211<=43

X112+X212<=40

X113+X213<=112

X114+X214<=231

X115+X215<=65

X116+X216<=27

X117+X217<=16

X118+X218<=73

X119+X219<=56

X120+X220<=88

X121+X221<=29

X122+X222<=21

X123+X223<=38

X124+X224<=42

X125+X225<=41

X126+X226<=49

X127+X227<=18

X128+X228<=116

X129+X229<=30

X130+X230<=22.

Model for an open economy

Objective Function

MIN 22282X11+49509X12+51168X13+11251X14+34585X15+15348X16+24842X17+25499X18+26931X19+20120X110+18263X111+15362X112+22842X113+16381X114+19493X115+15934X116+26495X117+25739X118+6757X119+13456X120+18042X121+10104X122+20197X123+33333X124+41904X125+18344X126+13872X127+11987X128+12903X129+23480X130+17745X21+44647X22+46554X23+4691X24+30061X25+10486X26+19980X27+20965X28+22068X29+15586X210+13726X211+10502X212+18303X213+11518X214+14923X215+11071X216+21633X217+20880X218+6648X219+8591X220+13500X221+5783X222+15660X223+28796X224+37046X225+13809X226+9010X227+7129X228+6346X229+18946X230+9530X31+31437X32+33336X33+24273X34+21846X35+9478X36+14564X37+3244X38+14153X39+7366X310+5352X311+9190X312+6766X313+8086X314+4436X315+9472X316+8424X317+15466X318+15561X319+11196X320+7824X321+25551X322+10491X323+15590X324+24161X325+13522X326+10828X327+12483X328+26412X329+10731X330+24749X41+51651X42+53553X43+2149X44+37065X45+17491X46+26984X47+27966X48+29073X49+22260X410+20405X411+17504X412+25307X413+18520X414+21602X415+18076X416+28637X417+27886X418+13652X419+15596X420+20179X421+4123X422+22664X423+35475X424+44046X425+20813X426+16017X427+14130X428+534X429+25947X430.

Offer restrictions

X11+X12+X13+X14+X15+X16+X17+X18+X19+X110+X111+X112+X113+X114+X115+X116+X117+X118+X119+X120+X121+X122+X123+X124+X125+X126+X127+X128+X129+X130=270

X21+X22+X23+X24+X25+X26+X27+X28+X29+X210+X211+X212+X213+X214+X215+X216+X217+X218+X219+X220+X221+X222+X223+X224+X225+X226+X227+X228+X229+X230=578

X31+X41+X32+X42+X33+X43+X34+X44+X35+X45+X36+X46+X37+X47+X38+X48+X39+X49+X310+X410+X311+X411+X312+X412+X313+X413+X314+X414+X315+X415+X316+X416+X317+X417+X318+X418+X319+X419+X320+X420+X321+X421+X322+X422+X323+X423+X324+X424+X325+X425+X326+X426+X327+X427+X328+X428+X329+X429+X330+X430=766.

Demand constraints

X11+X21+X31+X41=18

X12+X22+X32+X42=47

X13+X23+X33+X43=10

X14+X24+X34+X44=12

X15+X25+X35+X45=10

X16+X26+X36+X46=74

X17+X27+X37+X47=50

X18+X28+X38+X48=128

X19+X29+X39+X49=25

X110+X210+X310+X410=83

X111+X211+X311+X411=43

X112+X212+X312+X412=40

X113+X213+X313+X413=112

X114+X214+X314+X414=231

X115+X215+X315+X415=65

X116+X216+X316+X416=27

X117+X217+X317+X417=16

X118+X218+X318+X418=73

X119+X219+X319+X419=56

X120+X220+X320+X420=88

X121+X221+X321+X421=29

X122+X222+X322+X422=21

X123+X223+X323+X423=38

X124+X224+X324+X424=42

X125+X225+X325+X425=41

X126+X226+X326+X426=49

X127+X227+X327+X427=18

X128+X228+X328+X428=116

X129+X229+X329+X429=30

X130+X230+X330+X430=22.

Once the objective function and the respective supply and demand restrictions for each of the models were proposed, they were resolved using the Linear, Interactive, and Discrete Optimizer package (Lindo).

Results and discussion

In 2015, the national production of cocoa in Mexico was 28 006.59 t (SIAP, 2018), exports were of 133.83 t and imports totaled 23 521.37 t (SIAVI, 2018), so the national apparent consumption was 51 394.13 t. The total population of Mexico, in that year, was 119 938 472 inhabitants (INEGI, 2018), therefore, the apparent per capita consumption of cocoa in the country was 0.43 kg, this figure coincides with that presented in the Agroalimentary Atlas 2016 of the SIAP (SAGARPA, 2016).

Given that cocoa, in 2015, was only produced in the states of Tabasco, Chiapas and Guerrero, and in the latter the production was not enough to supply the state consumption of this crop, they are considered as national supplying states only to Tabasco and Chiapas, with a volume of 17 363.57 and 7 143.91 t respectively, once their domestic demand has been met. Table 1 shows the calculation of the deficit or surplus of cocoa of each state in tons of product, also has a column that

was called equivalence that refers to the number of trucks that supply or demand each state. The total amount of trucks in surplus was 848, while in deficit were 1 614 trucks, so it was necessary to import 766 trucks to fulfill the feasible solution property in programming.

Table 1. Classification of states (demandant and suppliers).

Key

State

Production (t)

Consumption (t)

Deficit (t)

Superavit (t)

Equivalence

(truck)

D1

Aguascalientes

0

563.93

563.93

-

18

D2

Baja California

0

1 435.02

1 435.02

-

47

D3

Baja California Sur

0

307.83

307.83

-

10

D4

Campeche

0

386.62

386.62

-

12

O1

Chiapas

9 387.43

1 269.1

-

8 118.33

270

D5

Chihuahua

0

306.42

306.42

-

10

D6

Ciudad de Mexico

0

2 240.52

2 240.52

-

74

D7

Coahuila de Zaragoza

0

1 529.54

1 529.54

-

50

D8

Colima

0

3 850.25

3 850.25

-

128

D9

Durango

0

754.1

754.1

-

25

D10

Guanajuato

0

2 513.08

2 513.08

-

83

D11

Guerrero

225.71

1 517.85

1 292.14

-

43

D12

Hidalgo

0

1 226.79

1 226.79

-

40

D13

Jalisco

0

3 376.84

3 376.84

-

112

D14

Mexico

0

6 952.65

6 952.65

-

231

D15

Michoacán

0

1 970.73

1 970.73

-

65

D16

Morelos

0

819.39

819.39

-

27

D17

Nayarit

0

509.35

509.35

-

16

D18

Nuevo León

0

2 199.06

2 199.06

-

73

D19

Oaxaca

0

1 703.86

1 703.86

-

56

D20

Puebla

0

2 649.58

2 649.58

-

88

D21

Querétaro

0

875.8

875.8

-

29

D22

Quintana Roo

0

645.24

645.24

-

21

D23

San Luis Potosí

0

1 167.15

1 167.15

-

38

D24

Sinaloa

0

1 275.7

1 275.7

-

42

D25

Sonora

0

1 231.69

1 231.69

-

41

O2

Tabasco

18 393.45

1 028.82

-

17 364.63

578

D26

Tamaulipas

0

1 479.85

1 479.85

-

49

D27

Tlaxcala

0

546.01

546.01

-

18

D28

Veracruz

0

3 482.81

3 482.81

-

116

D29

Yucatán

0

900.83

900.83

-

30

D30

Zacatecas

0

677.71

677.71

-

22

Elaboration with data from the SIAP and INEGI.

Under conditions of a closed economy, production and distribution must be efficient for the country, but this does not guarantee that the entire product is consumed, in that case there is a excess of production that can be subjected to an agro-industrial process to obtain by-products; or, export it through international trade (Ayllón et al., 2015). In the case of cocoa, production does not supply domestic demand, therefore, international trade is also used, but in the sense of acquiring abroad the quantity of product necessary to cover domestic demand.

In the Table 2 shows the transportation costs of the two national origins, considering the place of production and two international origins, considering two possible ports of entry for international cocoa.

Table 2. Transportation costs of national and international origins.

Key

Tapachula, Chiapas O1 ($)

Villahermosa, Tabasco O2 ($)

Lázaro Cárdenas, Jalisco O3 ($)

Puerto Progreso, Yucatán O4 ($)

D1

22 282

17 745

9 530

24 749

D2

49 509

44 647

31 437

51 651

D3

51 168

46 554

33 336

53 553

D4

11 251

4 691

24 273

2 149

D5

34 585

30 061

21 846

37 065

D6

15 348

10 486

9 478

17 491

D7

24 842

19 980

14 564

26 984

D8

25 499

20 965

3 244

27 966

D9

26 931

22 068

14 153

29 073

D10

20 120

15 586

7 366

22 260

D11

18 263

13 726

5 352

20 405

D12

15 362

10,502

9 190

17 504

D13

22 842

18 303

6 766

25 307

D14

16 381

11,518

8 086

18 520

D15

19 493

14 923

4 436

21 602

D16

15 934

11 071

9 472

18 076

D17

26 495

21 633

8 424

28 637

D18

25 739

20 880

15 466

27 886

D19

6 757

6 648

15, 61

13 652

D20

13 456

8 591

11 196

15 596

D21

18 042

13 500

7 824

20 179

D22

10 104

5 783

25 551

4 123

D23

20 197

15 660

10 491

22 664

D24

33 333

28 796

15 590

35 475

D25

41 904

37 046

24 161

44 046

D26

18 344

13 809

13 522

20 813

D27

13 872

9 010

10 828

16 017

D28

11 987

7 129

12 483

14 130

D29

12 903

6 346

26 412

534

D30

23 480

18 946

10 731

25 947

Elaboration with data from GlobalMap.

The total number of trucks that must be distributed nationwide to cover the apparent demand of all states is 1 614; however, in the case of the analysis of a closed economy, the available number of trucks in Mexico in 2015 was 848, so there is a deficit of 766 trucks (Table 3). According to the results of the programming carried out to reduce the transportation costs of cocoa, considering only the national production, the value of the objective function is $9 500 068.00.

Table 3. Cocoa distribution under closed economy.

Variable

Origin

Destination

Quantity (truck)

X111

Chiapas

Guerrero

43

X115

Chiapas

Michoacán

14

X119

Chiapas

Oaxaca

56

X121

Chiapas

Querétaro

29

X122

Chiapas

Quintana Roo

21

X126

Chiapas

Tamaulipas

49

X128

Chiapas

Veracruz

58

X24

Tabasco

Campeche

12

X26

Tabasco

Mexico City

74

X212

Tabasco

Hidalgo

40

X214

Tabasco

Mexico State

231

X216

Tabasco

Morelos

27

X220

Tabasco

Puebla

88

X227

Tabasco

Tlaxcala

18

X228

Tabasco

Veracruz

58

X229

Tabasco

Yucatán

30

Total

848

Elaboration based on the results of the Lindo program.

According to the results of the programming carried out to reduce the transportation costs of cocoa, considering an open economy, the value of the objective function is $18 123 640. Table 4 shows what the optimal distribution would be by reducing the costs of transport.

Table 4. Distribution of cocoa under open economy.

Variable

Origin

Destination

Quantity (truck)

Variable

Origin

Destination

Quantity (truck)

X119

Chiapas

Oaxaca

56

X32

Jalisco

Baja California

47

X121

Chiapas

Querétaro

29

X33

Jalisco

Baja California Sur

10

X122

Chiapas

Quintana Roo

21

X35

Jalisco

Chihuahua

10

X123

Chiapas

San Luis Potosí

38

X37

Jalisco

Coahuila de Zaragoza

50

X126

Chiapas

Tamaulipas

49

X38

Jalisco

Colima

128

X128

Chiapas

Veracruz

77

X39

Jalisco

Durango

25

X24

Tabasco

Campeche

12

X310

Jalisco

Guanajuato

83

X26

Tabasco

Ciudad de Mexico

74

X311

Jalisco

Guerrero

43

X212

Tabasco

Hidalgo

40

X313

Jalisco

Jalisco

112

X214

Tabasco

Estado de Mexico

231

X315

Jalisco

Michoacán

65

X216

Tabasco

Morelos

27

X317

Jalisco

Nayarit

16

X218

Tabasco

Nuevo León

49

X318

Jalisco

Nuevo León

24

X220

Tabasco

Puebla

88

X324

Jalisco

Sinaloa

42

X227

Tabasco

Tlaxcala

18

X325

Jalisco

Sonora

41

X228

Tabasco

Veracruz

39

X330

Jalisco

Zacatecas

22

X31

Jalisco

Aguascalientes

18

X429

Yucatán

Yucatán

30

Elaboration based on the results of the Lindo program.

The reduced costs show all the routes that were not selected by the model in the optimal solution, whose value is different from zero. The interpretation of these values indicated that by introducing these routes the value of the objective function would increase. For example, transporting a truck with cocoa from Chiapas to Aguascalientes (X11) would raise the value of the objective function by $2 789.00 pesos, in the same way, forcing the model to transport a cocoa truck from Chiapas to Baja California (X12) would raise the value of the objective function in $30 016.00 pesos.

Conclusions

The national production of cocoa in Mexico in 2015 was insufficient to satisfy domestic consumption, so imports of this product were made, the national apparent consumption was 51.3 thousand tons. Under the system of closed economy, it will only be able to distribute 848 trucks, so minimizing transport costs only the states of central-south of the country could fully meet their demand for this grain, while Michoacán can get 14 of the 65 truck that demand. The optimal cost of transportation with a closed economy was $9.5 million pesos.

In order to cover the national demand for cocoa, it is necessary to resort to foreign markets, which is why the port of Lazaro Cardenas, Jalisco, turned out to be a viable option, while Puerto Progreso, Yucatán was only feasible to supply the demand of its state; therefore, it is not a viable option for the importation of cocoa. The optimum cost of the market with an open economy was $18.1 million pesos.

Finally, it is recommended to carry out the transport model considering the agroindustrial demand of this crop in each state since, being a crop that is part of the chocolate production chain, the industry has great weight in the demand for it. In addition, a new model can be run considering other ports in the Gulf of Mexico.

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