Transportation refers to the movement of product from one location to another as it makes its way from he beginning Of a supply chain to the customer. Transportation is an important supply chain driver because products are rarely produced and consumed in the same location. Transportation networks are complex, large- scale systems, and come in a variety of forms, such as road, rail, air, and waterway networks. Transportation networks provide the foundation for the functioning of economies and societies through the movement of people, goods, and services.
Any supply Chain’s success is closely linked to the appropriate use of transportation. California growers face major competition from South American growers. South American growers have many competitive advantages, including the favorable trucking rates they enjoy by consolidating all shipments in Miami, Florida, prior to US distribution. A competitive advantage for South American growers is that they implemented the cross docking and distribution facility which is shared in Miami and Florida.
However the California growers ship their products from individually to the customers and few California growers get the advantage of ordering the large volume in quantities and get advantage over the price. Because of having no common pickup location Californians flower farms grow, sell, and hip their products independently. A Carrier must go to these locations to pick up orders. On the other hand, South American growers pay for shipping costs, California growers pass on these costs to their customers.
If California growers can decrease transportation costs, they can pass these savings on to their customers and provide an added incentive to purchase California cut flowers. Based on how they handle transportation, customers can be classified into two broad categories: (1 ) Wholesale markets that enter into long-term shipping arrangements with third-party carriers. Products bound or different wholesale purchasers can be accommodated on the same truck. 2) Mass markets that employ their own transportation network; thus, flowers purchased by different mass market customers travel in separate trucks The authors faced a number of difficulties while writing this paper. The primary one was the fact that flowers are a highly perishable product where product quality and freshness is of high importance. They had to consider both the consolidation strategy and permissibility of the product over a sufficiently long planning horizon. They had a hard limit on the amount of time the flowers spent in transit and inventory.
The second one was on the data collection, in 201 0, 70 growers reported production sales totaling $220 million to CUFF. Of these 70 cut flower producers, only 16 participated in the transportation study. Seven growers provided demand data for both 2008 and 2010. Four growers participated only in the 2008 study, which is to say that not all the growers participated Due to the lack of data; the authors had to extrapolate data that is subject to greater uncertainty and has a higher risk of producing meaningless results. The authors had to come up with a lot of assumptions during the data analysis phase.
Also, the authors leave out real life business scenarios, for instance the consolidation model does not consider a limited transportation fleet or a finite storage capacity at the consolidation center and how the cost is being allocated among the participating firms is unclear. They also do not consider the cost incurred by each farm when they A fair cost allocation may be achievable only by providing incentives to larger growers to accumulate enough volume to enjoy economies of scale. With the participation of growers on larger farms, those on the small to medium-sized farms can reap the benefits of consolidation.
Without the participation of larger growers, such consolidation practice will not give rise to benefits as large as predicted by the model. Without the volume provided by larger farms, the consolidation center would have too many opportunities to utilize the cost effective OFT trucks. Optimization Model Formulation: parameterizes, Cuff is the transportation cost for a full truck from consolidation center to destination. This multiplied by Exit which is the number of full trucks from consolidation center to destination gives us the total cost of transporting all full trucks from consolidation center to destination.