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The selection of locations for the eBeam facilities is driven by transportation, re- sources (labor, materials, and utilities), taxes, and regulations. This section discusses these factors to develop a factor rating system (FRS) for the eBeam facility location alternatives and to analyze each factor’s impact on the setup cost, the operating cost, and the unit transportation costs.

Table 4.17: Factor Rating System for Eight Potential Locations.

Factor Trans. Constr. Labor Trade Electr. Tax Border Total

Conv. Cost Cost Activity Rate Rate Delay Points

Point Range 0 to 300 0 to 200 0 to 100 0 to 100 0 to 60 0 to 30 0 to 50 0 to 840 Nuevo Laredo 260 120 90 90 55 25 5 645 Houston 250 120 65 80 45 20 30 610 Matehuala 170 190 85 45 55 25 30 600 San Antonio 250 120 60 55 45 20 30 580 Reynosa 185 120 85 70 55 25 40 580 Laredo 245 120 60 85 45 20 5 580 Dallas 250 120 65 45 45 20 30 575 Matamoros 180 120 80 50 55 25 45 555

We collect data from the U.S. Census Bureau, the U.S. Bureau of Labor Statis- tics, the Bureau of Transportation Statistics, the U.S. Energy Information Admin- istration, and the U.S. Customs and Border Protection (CBP). We focus on border entry/crossing data, North American transborder freight data, labor force data for both Mexico and the U.S., U.S. exports and imports trade activity, industrial elec- tricity rates for Texas and Mexico, and border wait times data. The detailed results of the FRS (Table 4.17) for the eight potential locations indicate that Nuevo Laredo is the best location to build an eBeam facility. It has the highest score for almost all factors. Houston’s high ratings in transportation convenience and trade activity place it above other locations in the U.S. Matehuala, San Antonio, Reynosa, and Laredo rank behind the two leaders. The results of this analysis are very similar to the results of Section 4.5.

To estimate the fixed setup cost, we collect the estimated construction costs for all potential locations from the National Center for Electron Beam Research. The approximate construction costs indicate that it is slightly less expensive to build an eBeam facility in Mexico than in the U.S. However, because this difference is so small, we use the same fixed setup cost for each. The only exception is Matehuala, which already has a gamma ray radiation facility that can be converted to an eBeam facility at a lower cost.

The border crossing delay time at each border crossing point depends on the number of truckloads crossing it and its number of Verification and Inspection Points (VIPs). Nuevo Laredo is strategically positioned at the convergence of several high- ways, railroads, and bridges. It is considered to be Mexico’s most important inland port for exporting agricultural products to the U.S. (USDA 2015a). Between 2013 and 2015, Nuevo Laredo/Laredo, even though it has only five VIPs, accounts for over two thirds of all imports (truckloads of commodities) from Mexico. Colombia/Laredo

has four VIPs, Ciudad Juarez/El Paso has nine VIPs, and Reynosa/McAllen has seven VIPs (USDA 2015a). Thus, the average border waiting time is longest at Nuevo Laredo/Laredo. The border delay time estimates are collected from CBP Border Wait Times Data (2016) and Avetisyan et al. (2015).

Our MCF model decides to which eBeam facility and to which Texas hub each truck is assigned. The actual route for each truckload of fruit is determined by on-line mapping software, such as Google Maps, while respecting the prohibited movement areas for untreated commodities. The transportation cost between two locations in the MCF model is estimated based on these routes.

The per-line capacity and operating cost at each location are estimated using the Bureau of Labor Statistics Labor Force Data (2014), including the average revenue, the employment rate, and the annual tax report for the eight potential locations. As expected, the overall employment rate, the average labor cost, and the tax rate are all lower in Mexico than in the U.S. In addition, the average industrial electricity rate in Texas is $0.0557/kWh and in Mexico is $0.0502/kWh. We calculate the capacity and operating cost by aggregating amortized setup cost, labor cost, tax, and electricity consumption. The resulting capacity and operating cost in Mexico is set lower than that in the U.S. (see Table 4.7).

4.7 Conclusion

The amount of fresh produce crossing the U.S. / Mexico border has increased ex- ponentially since the implementation of the North American Free Trade Agreement in 1994. Imported fresh produce must be treated for pestilence and microbial pathogen contamination. This requirement protects the health of those who consume the pro- duce and the viability of domestic crops that could be infested by pests or infected by those pathogens. Among the various technologies that have been used for this

function—freezing, heat treatments, chemical fumigation, and irradiation—electron beam (eBeam) irradiation is relatively new and has many advantages, including high throughput, high dose rate, low capital investment, and low operating costs. Fur- thermore, it requires only commercial electricity (rather than, for example, gamma ray radiation from cobalt-60), which it uses efficiently.

This study provides guidelines for private industry in the U.S. and Mexico to select the most cost-efficient locations for the eBeam facilities specifically designed for phytosanitary treatment of fresh fruits and vegetables crossing the Texas/Mexico border. It also determines how many service lines (one eBeam machine per line) each facility should have. The produce is grown in seven Mexican states and is shipped to three hubs in Texas. Thus, our algorithm assigns each truck leaving a growing region to an eBeam facility and to a hub so that costs are minimized. The study incorporates the unique characteristics of the problem, such as eBeam irradiation technology, multiple commodities, prohibited movement areas in Texas, regulation and infrastructure issues, delays at border crossing points, and queueing delays at the eBeam facilities. To capture all factors that a manager must consider, the cost objective includes the fixed set-up cost for building each eBeam facility; each facility’s operating cost, which depends on the number of service lines selected; the transportation, processing, and border delay costs; and the queuing delay cost, which is determined by the number of service lines and the number of truckloads assigned to each facility.

We developed a generalizable decision support system that uses a heuristic that is based on a minimum cost flow model (MCF). This polynomial-time heuristic consid- ers all possible combinations of locations for the eBeam facilities (from eight candi- date locations). For each such combination, the MCF optimizes the transportation, processing, and border delay costs. For each facility within this combination, the

heuristic determines the number of service lines that minimizes the operating and queueing delay costs.

Both the computational study and the factor rating analysis suggest that Nuevo Laredo (Mexico) is the best location to build an eBeam facility overall. This is because all traffic is routed to the Nuevo Laredo / Laredo border crossing, and oper- ating a facility in Mexico is less expensive. In addition to Nuevo Laredo, Matehuala (Mexico) is also highly rated. Houston and San Antonio are the two best locations for building eBeam facilities in the U.S. Overall, if building no more than two eBeam facilities, selecting locations in Mexico has lower total cost than selecting them in the U.S.

In summary, our analysis provides an effective importing and distribution plan- ning tool that integrates multiple decisions for selecting sites for phytosanitary fa- cilities along the Texas/Mexico border by considering new food safety technology and key economic factors that signal local growth and development. The methodol- ogy developed in our problem is general enough to be applicable to a wide variety of food distribution networks in other countries or to similar contexts with minor modifications.