Author
Listed:
- Lawrence D. Burns
(General Motors Research Laboratories, Warren, Michigan)
- Randolph W. Hall
(General Motors Research Laboratories, Warren, Michigan)
- Dennis E. Blumenfeld
(General Motors Research Laboratories, Warren, Michigan)
- Carlos F. Daganzo
(University of California, Berkeley, Berkeley, California)
Abstract
This paper develops an analytic method for minimizing the cost of distributing freight by truck from a supplier to many customers. It derives formulas for transportation and inventory costs, and determines the optimal trade-off between these costs. The paper analyzes and compares two distribution strategies: direct shipping (i.e., shipping separate loads to each customer) and peddling (i.e., dispatching trucks that deliver items to more than one customer per load). The cost trade-off in each strategy depends on shipment size. Our results indicate that, for direct shipping, the optimal shipment size is given by the economic order quantity (EOQ) model, while for peddling, the optimal shipment size is a full truck. The peddling cost trade-off also depends on the number of customers included on a peddling route. This trade-off is evaluated analytically and graphically. The focus of this paper is on an analytic approach to solving distribution problems. Explicit formulas are obtained in terms of a few easily measurable parameters. These formulas require the spatial density of customers, rather than the precise locations of every customer. This approach simplifies distribution problems substantially while providing sufficient accuracy for practical applications. It allows cost trade-offs to be evaluated quickly using a hand calculator, avoiding the need for computer algorithms and mathematical programming techniques. It also facilitates sensitivity analyses that indicate how parameter value changes affect costs and operating strategies.
Suggested Citation
Lawrence D. Burns & Randolph W. Hall & Dennis E. Blumenfeld & Carlos F. Daganzo, 1985.
"Distribution Strategies that Minimize Transportation and Inventory Costs,"
Operations Research, INFORMS, vol. 33(3), pages 469-490, June.
Handle:
RePEc:inm:oropre:v:33:y:1985:i:3:p:469-490
DOI: 10.1287/opre.33.3.469
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