Facility Location Problem of Beverage Distribution Considering Time Window and Land Use Plan Using GIS

As the boundaries and population of urban areas expand, beverage distributors may seek to expand the capacity in their distribution centers. As a result, they may need to add new locations or increase the utilization of their existing center. This paper investigates the facility location problem through network space, considering traversable truck roads, thereby providing a strategic decision for identifying a depot location in consideration of vehicle routings from a real application. For the analysis, a geospatial tool, which is embedded in the commercial software ArcMap®, was used for routing and calibrating the model. Ten candidates from commercial and industrial zones in the cities of Fargo, West Fargo, and Moorhead were considered for future distribution centers. The candidate locations were analyzed to determine which site minimizes the total transportation costs and travel miles in consideration of time window, vehicle capacity, heterogeneous vehicle types, land use plan, and hours-of-service. Most attractive candidates are close to the intersections of major highways. From the analysis, the study recommends locating a distribution center at three alternatives based on the average ranking method. This study can be used by distributors as they consider new locations and extra depots to support strategic planning to deal with mid-term and long-term growth of demand in beverage markets. This study provides a ready-to-use example of how to adopt state-of-the-art spatial technology and operations research using Geographic Information Systems (GIS), and bring it to state-of-practice

Trip Generation Rates for Large Elevators: A North Dakota Case Study

Large grain elevators are major sources of truck traffic in many areas. Shuttle trains, a recent railroad innovation, have further concentrated truck deliveries at larger elevators. These facilities—which have not been analyzed in previous trip generation studies—pose issues such as large truck access and pavement design. In this paper, elevator trip generation equations are estimated from detailed facility, land use, and highway traffic data in North Dakota. A trip attraction equation is used to explain the effects of elevator storage capacity and side track capacity on elevator throughput. Elevators are classified on the basis of track capacity as shuttle train, unit train, and multicar. Shuttle-train elevators typically consign 110-car trains, while unit-train elevators consign 50- to 100-car trains. The analysis shows that large shuttle-train elevators may generate 35,000 to 40,000 loaded and empty truck trips per year. A large unit-train elevator may generate 20,000 annual trips. The trucks are usually a mixture of combination five-axle and single-unit trucks. On average, each truck generates 1.04 equivalent single-axle loads on flexible pavements. Thus, a large facility may generate much of the traffic load experienced by pavements in the area. Moreover, truck deliveries to elevators exhibit seasonal variation. Approximately 15% of the annual volume is delivered during the peak month. Thus, a large shuttle facility may generate 225 trucks per day during the peak harvest month