Distribution Network Configuration Considering Inventory Cost

Inter-city distribution network structure is considered as one of which determine the quantity of economic activities in each city. In the field of operations research, several types of optimal facility location problem and algorithms for them have been proposed. Such problems typically minimize the logistic cost with given inter-city transportation cost and facility location cost. But, when we take inventory to coop with fluctuating demands into account, facility size becomes different for each location reflecting the level of uncertainty of demand there. As observed in many developed countries, customers require more variety of commercial goods, and we must prepare more number of commercial goods. Moreover, life length of each product becomes shorter. Without highly organized management, large inventory for many products yield large risk of depreciation of commercial value as well as large cost for floor space for stocking. Considering those, inventory cost should be explicitly considered in distribution network configuration problem. There is an essential trade off between inventory cost and transportation cost: when you set smaller number of distribution center having thicker demands there, relative stock size to coop with fluctuations become small and then, we need less inventory cost. But such concentrated location pattern results longer transportation to the customers and larger transportation cost. Nozick and Turnquist(2001) formulated a two-echelon distribution network formation problem considering inventory cost at plant and distribution centers. They used optimal inventory assignment considering the expected penalty of distribution center stock-out and plant stock-out. Stock-out was considered as the situation when Poisson distributed demand exceeded stock size, and the mean demand there was given by optimal facility location model. Inventory size of distribution center alters the location cost of distribution center, therefore optimal facility location problem was refreshed and solved again. The paper proposed iterative algorithm to get optimal inventory locations. Our paper expands their model in two ways; first we admit the difference of unit location cost for distribution centers by geographical locations, and secondly, we consider different uncertainties for customer orders by departing from simple Poisson distribution. The first alternation gives new explanation for the following situations: highly dense metropolitan regions have relatively larger number of centers and smaller coverage of each center. But such propensity usually contradicts with the land price; then center location should be limited considering higher land price in metropolitan areas. Then the optimal locations cannot be prospected in straight forwardly. The second model expansion allows our model to analyze how regularity of demands affects on the network structure. Our paper applies the model to the realistic Japanese transportation network, and show which cities may possess distribution center function in the nationwide distribution network. Without the back-stock in plant level, each distribution center must prepare inventory for their demand, but such inventory sometime requires unrealistic large location cost in metropolitan area such as Tokyo. On the other hand, if distribution center can rely on the back stock in plant, the centers in metropolitan regions stand without their own inventory.

A Windowed Transportation Planning Model

This research develops and applies a transportation planning model that integrates regional and local area forecasting approaches. While regional models have the scope to model the interaction of demand and congestion, they lack the spatial detail of a local approach. Local approaches typically do not consider the feedback between new project traffic and existing levels of traffic. Using a window, which retains the regional trip distribution information and the consistency between travel demand and congestion, allows the use of a complete transportation network and block level traffic zones while retaining computational feasibility. By combining the two methods, a number of important policy issues can be addressed, including the implications of traffic calming, changes in flow due to alternative traffic operation schemes, the influence of micro-scale zoning changes on nearby intersections, the impact of TDM on traffic congestion, and the consequences of a suburban light rail line.transportation planning model, traffic impact study, travel demand model, intersection control, window .

Transport cost and endogenous quality choice

This paper examines how the quality of exports depends on relative country size and its remoteness. Specific transportation cost is the key variable in our analysis as it gives rise to the Alchian-Allen effect. In the model, we allow for endogenous quality choice by a producer serving many international locations. Higher quality comes at higher marginal cost of production, but can be delivered at the same absolute, and thus proportionally lower, transportation cost to a given destination. Our model complements the well documented demandside response to the distribution of transportation costs (known as the Alchian-Allen effect) by the supply side response. We show that, ceteris paribus, equilibrium quality decreases in the domestic country size and increases in remoteness from foreign markets. This happens because a larger portion of the demand is affected by the Alchian-Allen effect for smaller countries’ producers, and the Alchian-Allen effect is stronger for remote countries. We confirm our predictions empirically on a detailed product level dataset of all exporters worldwide into a sample of Latin American importers

Optimization Of Bread Distribution Transportation Costs At Ud Bakery Garden Using The MDMA Method (Maximum Divide Minimum Alloment)

This study aims to optimize distribution transportation costs using a transportation model. The transportation model is a model that aims to determine the number of goods that must be sent from source to destination so that total transportation costs can be optimized. The transportation model used in this study is the Maximum Divide Minimum Aloment (MDMA) method. Data collection is in progress using Maximum Divide Minimum Aloment (MDMA), namely data on fixed costs, variable costs, demand and capacity of goods. The results of optimization research using the Maximum Divide Minimum Aloment (MDMA) method were obtained at Rp. 24,541,890 and has a difference with the costs incurred by the company of Rp. 3,449,660. Therefore, the MDMA (Maximum Divide Minimum Aloment) method can solve problems or can be used to minimize transportation costs

Transport Cost and Endogenous Quality Choice

This paper examines how the quality of exports depends on relative country size and its remoteness. Specific transportation cost is the key variable in our analysis as it gives rise to the Alchian-Allen effect. In the model, we allow for endogenous quality choice by a producer serving many international locations. Higher quality comes at higher marginal cost of production, but can be delivered at the same absolute, and thus proportionally lower, transportation cost to a given destination. Our model complements the well documented demandside response to the distribution of transportation costs (known as the Alchian-Allen effect) by the supply side response. We show that, ceteris paribus, equilibrium quality decreases in the domestic country size and increases in remoteness from foreign markets. This happens because a larger portion of the demand is affected by the Alchian-Allen effect for smaller countries’ producers, and the Alchian-Allen effect is stronger for remote countries. We confirm our predictions empirically on a detailed product level dataset of all exporters worldwide into a sample of Latin American importers.

Utilization of Transportation Model for Profit Maximization for Strategic Cement Sdn Bhd

This project is entitled' Utilization of Transportation Model for profit maximization for Strategic Cement Sdn Bhd '. Transportation Model in this project is one class of linear programming which is one of the decision tool for solving problem in management science. The transportation model utilized in this project is based _on the modelling developed by Anderson et. af. . The objective of this project is to determine the optimum delivery schedule of cement from two plants of Strategic Cement Sdn Bhd to fulfill the demand of twenty three different locations/destinations in Peninsular Malaysia. The factors involved in determining the profit maximization of the company are cement selling price to the various destinations, production cost, paper bag cost, stevedoring cost, commission to distributors and transportation cost. The result generated by the Model shows that the optimum distribution pattern is following the profit or revenue maximum pattern i.e. delivery of cement to the maximum profit contribution areas. The trade-off in the Transportation Model is the unsatisfied or unfulfilled demand area or market share which will in tum affect customer satisfaction level. The current practice by Strategic Cement Sdn Bhd reveals that company is supplying to certain demand location/destination despite with lower profit margin as compared to the empirical result generated/guided by the Transportation Model. This is mainly attributed to the fact that in the real business world, other factors shall be taking into consideration besides profits , such as customer service, market share and long term business relationship.The sensitivity analysis reveals that 1% change of the variables and demand has direct effect on the profit margin and transportation schedule for the company. Management of Strategic Cement Sdn Bhd can therefore utilizes this information to control cost and delivery schedule to achieve higher profit margin

Projected Demand and Potential Impacts to the National Airspace System of Autonomous, Electric, On-Demand Small Aircraft

Electric propulsion and autonomy are technology frontiers that offer tremendous potential to achieve low operating costs for small-aircraft. Such technologies enable simple and safe to operate vehicles that could dramatically improve regional transportation accessibility and speed through point-to-point operations. This analysis develops an understanding of the potential traffic volume and National Airspace System (NAS) capacity for small on-demand aircraft operations. Future demand projections use the Transportation Systems Analysis Model (TSAM), a tool suite developed by NASA and the Transportation Laboratory of Virginia Polytechnic Institute. Demand projections from TSAM contain the mode of travel, number of trips and geographic distribution of trips. For this study, the mode of travel can be commercial aircraft, automobile and on-demand aircraft. NASA's Airspace Concept Evaluation System (ACES) is used to assess NAS impact. This simulation takes a schedule that includes all flights: commercial passenger and cargo; conventional General Aviation and on-demand small aircraft, and operates them in the simulated NAS. The results of this analysis projects very large trip numbers for an on-demand air transportation system competitive with automobiles in cost per passenger mile. The significance is this type of air transportation can enhance mobility for communities that currently lack access to commercial air transportation. Another significant finding is that the large numbers of operations can have an impact on the current NAS infrastructure used by commercial airlines and cargo operators, even if on-demand traffic does not use the 28 airports in the Continental U.S. designated as large hubs by the FAA. Some smaller airports will experience greater demand than their current capacity allows and will require upgrading. In addition, in future years as demand grows and vehicle performance improves other non-conventional facilities such as short runways incorporated into shopping mall or transportation hub parking areas could provide additional capacity and convenience

A BI-LEVEL SCHEME FOR ASSESSING THE IMPACT OF AIR TRANSPORTATION ON LOCAL DEVELOPMENT

An approach to assess the impact of the creation or expansion of an air transport infrastructure over regional development is proposed in this paper. Effective long term planning of this costly investment requires performing an overall analysis of socio-economic consequences through long term forecasting, scenario generation and risk analysis. One of main aspects of this task is related with the estimation of future demand over the modified transportation network which attends the considered region. The proposed approach makes use of two complementary models: One model is devoted to demand forecasting taking into account the modified accessibility of the multimodal transportation network, the other one defines the global transport supply according to a profit maximization behavior for the involved transport system. The demand forecasting process is based on an entropy maximization approach with flexible origin-destination levels to determine the intensity and the distribution of new origin-destination vectors. A two level solution technique considering vehicle flows at the first level and the payload/passengers flows at the second level is introduced. The proposed solution scheme is composed of an iterative process between the current solution for demand forecasting and the supply optimization problem: the entropy maximizing distribution problem provides the origin-destination matrix given a cost/capacity structure, while the supply optimization problem provides this cost/capacity structure resulting from the accessibility level, given the updated origin-destination vectors. The proposed approach is illustrated in the case of a fast developing rural agro-industrial area in central Brazil, where the consequences of the installation of a medium size airport are assessed.

Logistics Costs Based Estimation of Freight Transportation Demand

Many supply chain and fi nished goods distribution networks involve intercity freight transportation. Shipping customers secure transportation services by matching their requirements to available service in an effort to minimize their total logistics costs subject to service level constraints. Frequently, shippers' modal decisions are constrained by short-term capacity constraints restricting one of the available options, or gaps in shipper knowledge or carrier marketing programs. As a result, the observed traffic flows may not reflect the potential demand for the mode. Because the potential demand for a mode is not directly measurable, when planning road and rail capacity, governments and railroads cannot make accurate capacity planning decisions based on current traffic flows. The model developed here identifi es the potential demand for intercity full truckload and intermodal shipments over the most heavily utilized 75,000 shipment lanes in the western United States by estimating minimum total logistics costs by mode. These flows are compared with actual U.S. freight flows in order to determine the differences between observed flows and the model estimated potential demand. The results indicate potential demand for intermodal transportation is high; considerable freight volumes could be delivered with lower logistics cost by switching from truck to intermodal transportation. This evidence suggests that observed traffic flows and trends may not be a sound basis for planning freight transportation infrastructure in the United States