The approach used to solve the network design problem is based on a Benders' decomposition method where the sub-problem is a mixed integer programming problem. The master problem consists of choosing the best configuration $Q$ given the current set of constraints, where $Q$ is the warehouses capacity vector. Once this configuration is found, a cut is generated by searching for the smallest stable transportation cost for this configuration. The problem of finding the smallest stable transportation cost is itself solve by bender decomposition where the master problem search for the worst demand for the fixed configuration and the cut generating sub-problems are simple flow problems using fixed configuration and demands. This section first present some useful definitions, then successively proposes the formulations for the flow sub-problem, the stable transportation cost sub-problem and finally the global design problem. The distribution network contains mills, warehouses and customers zones. The problem, for every period, consist of transiting manufactured products through warehouses to the customers. The following definitions will be useful. The flow of products is defined by the two following set of variables. The quantity of product transiting from the mill to the warehouse. Since later we want to find a demand that maximizes the cost of the flow problem, it is useful to consider the dual of the previous problem in order to have a maximization objective function. where $lambda$, $alpha$, $mu$ and $sigma$ are, respectively, the dual variables of constraints ef{lambda}, ef{alpha}, ef{mu}, and ef{sigma}. We call $Phi(Q,d)$ the optimal value of the objective function for the linear program ( ef{FlowDual}). ... ... middle of paper ... ...st $r_j$, the variable inventory cost $i_j$ and the transportation cost $Phi(Q)$ knowing that we will have to face the worst demand for that network. A binary variable $o_j$ determines whether or not warehouse $j$ is open. To ensure that there is always enough space in the warehouses to fulfill any demand we require that $sum_{j in W} Q_j geq sum_{s in S} d_s$. The design problem is. Let $Delta$ be the finite set of possible value of the binary variables $delta^+, delta^-, w, f$ and let $h_r(delta) = (sigma_{r,delta},z_{r,delta},alpha_{r,delta},mu_{r,delta}), r = 1 ldots m_delta$ be the set of extreme points of the problem ( ef{WorstBin}) with the value of the binary variable fixed. Since problem ef{Design1} is convex with respect to variables $gamma$ we can use a Benders' decomposition approach to solve the following network design problem.
Another observation from the model is that, the demand for option AB is very high when compared with the other options. One alternative to prevent losing consumers of this product and at the same time counter the uncertainties of demand of product AB, HP could ship AB products via air. Before committing to air shipment for only product option AB, the company should first check if it is option AB that the DC in Europe is falling short. If yes what are the costs associated with losing that sale. If the costs associated with losing customers in that segment as very high when compared to the costs associated with air shipment then, HP could air ship the product whose demand is very high.
This constraint ensures that the hop-count for each node-pair (s, d) does not exceed the pre-specified bound〖 H〗_(s,d).
o Case 1: Maximum unknown a priori -- You have to search through the entire array to find the maximum. Thus, there is no worst case or best case if you consider the work as comparisons (dominant cost) only.
National Logistics Management is the only North American Third Party Logistics provider to specialize solely in premium freight for manufacturing industries, including automotive manufacturers. It is non-asset based and has a unique business model that employs its proprietary software to utilize the Internet to determine optimal shipping modes; export shipments to its vast carrier base including ground, air freight, and air charter; receive bids back form its carrier network; evaluate the lowest bids and carrier quality ratings; and coordinate shipments based on best price and carrier quality ratings all within a 30-minute window.
Lastly, the stores and warehouses are not communicating well which is resulting in confusion for both parties. Store managers waste time by having to spend store hours on the phone with the DC to expedite demanded stock. This time waste can be avoided by properly organizing the warehouse and having informed workers who can get the job done right and on time. Also worth mentioning is the current condition of the warehouse; there is inventory underneath conveyors and scattered across aisles, making it harder to track down stock.
Inside the Target Corporation there are many processes taking place every day. In this paper I will focus on the task of replenishment.
The Darby Company is re-evaluating its current production and distribution system in order to determine whether it is cost-effective or if a different approach should be considered. The company produces meters that measure the consumption of electrical power. Currently, they produce these meters are two locations – El Paso, Texas and San Bernardino, California. The San Bernardino plant is newer, and therefore the technology is more effective, meaning that their cost per unit is $10.00, while the El Paso plant produces at $10.50. However, the El Paso plant has a higher capacity at 30,000 to San Bernardino’s 20,000. Once manufactured, the meters are sent to one of three distribution centers – Ft. Worth, Texas, Santa Fe, New Mexico and Las Vegas. Due to the proximity of El Paso to Ft. Worth, they are only plant to ship to Ft. Worth. The costs associated with each shipment are described in detail in Appendix 2.2A. From these distribution centers, meters are shipped to one of nine customer zones. The Ft. Worth center services Dallas, San Antonio, Wichita and Kansas City, the Santa Fe center services Denver, Salt Lake City, and Phoenix, and the Las Vegas center ships to Los Angeles and San Diego.
This is basically a problem where we can check an easy possible solution, but that does not mean that is the most optimal solution. In order to find the best solution to the problem all the possibilities have to be considered and calculated.
Most of the uncontrollable cost items (e.g., charges to other network operators, or purchases of energy) were eliminated from the cost base and the level of remaining uncontrollable costs was minimal. The costs associated with the performance of transmission activities were removed from the analysis.
Coyle, J., Langley, C., Gibson, B., Novack, R. and Bardi, E. (2008).Supply Chain Management: A Logistics Perspective. 8th ed. Cengage Learning, p.366.
Matching demand and supply: The channel members will allocate the goods according to the demand.
In the Indian context, warehouses are necessary for the commodity sector and commodity future trading especially for farmers because agricultural commodities constitute a major segment of the Indian economy.
Zanjirani F., Rezapour, S. & Kardar, L. (2011) Logistics operations and management concepts and models, 1st ed. London ; Elsevier.
All choices made by Seven-Eleven are structured to lower its transportation and receiving costs. For example, its area-dominance strategy of opening at least 50 to 60 stores in an area helps with marketing but also lowers the cost of replenishment. All manufacturing facilities are centralized to get the maximum benefit of capacity aggregation and also lower the inbound transportation cost from the manufacturer to the distribution center (DC). Seven-Eleven also requires all suppliers to deliver to the DC where products are sorted by temperature. This reduces the outbound transportation cost because of aggregation of deliveries across multiple suppliers. It also lowers the receiving cost. The information infrastructure is set up to allow store managers to place orders based on analysis of consumption data. The information infrastructure also facilitates the sorting of an order at the DC and receiving of the order at the store. The key point to emphasize here is that most decisions by Seven-Eleven are structured to aggregate transportation and receiving to make both cheaper.