I Congresso da SBI-Agro


Logistics in Transport Corridors


Maria Inês Faé
Universidade Federal do Espírito Santo
Campus Universitário de Goiabeiras, Departamento de Engenharia de Produção
Centro Tecnológico, 29060-970 Vitória, Espírito Santo, Brasil
Telefone e fax 027 3352649 e 3352650



This paper presents a general logistic view of transport corridors, and pinpoint some of the technological information apparatus that is used to overcome the challenges of a supply chain management. The evolution steps of the logistic systems are shown, followed by the role of simulation software in dealing with problems of transport logistics. It is also shown the RECOPE project that has been carried on within a group of Brazilian Universities which aims to develop simulation methods to measure the transport corridors performance and to provide a tool able to support the decisions about investment and operation in the transport system.

Key words

Logistics in transport; simulation in transport; intermodal transport



Brazilian transport corridors are generally composed by various modes under the management of different operators. Due to the lack of integration policies, isolated modes may have high level of productivity while the transport corridor as a whole may be inefficient. Infrastructure deficiency, bureaucracy, and lack of appropriate supply chain management are usually related to the inefficiency of the brazilian transportation system. To make the intermodality effective, and the various activities of the supply chain efficient, it is of paramount importance the use of technological information on the logistic chain.

Until 1960, the various activities of the supply chain were isolated. Partial integration was observed from 1960 till 1990. During the 70's, demand studies and all activities related to raw material used in the production process were initially grouped on a department of materials supply, while other operational elements concerning the final product were subordinated to the responsibility of a physical distribution management. The availability and proliferation of new hardware, software, and telecommunications technologies have become available since 1980. Technology provides a means to cope with the increasing information intensity and complexity of the traffic management task that has appeared with the downsizing, inventory reduction, partnership, and quality (Faé, 1997a). Traffic function has been a major player in the ongoing evolution of logistics information systems. The automation of information processing and decision-making processes in the traffic management function is a general trend (Masters & La Londe, 1994). The "full" logistics is likely to occur when the supply chain management, and the effective consumer response, will be completely operating. This is the sign of the new century.

Table 1 shows the evolution of logistics since de 1960's.


fragmented until 1960 partial integration
1960-70 1980 - inner 1990 - outer
global integration
demand forecast        
supply activities        
production planning materials      
in-process inventory management bar code    
warehousing   third party supply-chain  
internal transport   just-in-time management logistics
material handling   EDI    
finished goods invent physical      
physical distribution distribution      
order processing management      
customer services        

Table 1 : Logistics evolution

Before the 60's, logistics were fragmented into the individual processes of supply, stock and distribution. Gradual chances during the 70's have grouped activities into two large sectors : materials management and physical distribution management. The materials group comprised raw material supply, goods in-process inventory, production planning and control, and material handling inside the organisation. Physical distribution were treated as the efficient movement of finished products to clients, comprising freight, warehousing, packing, and inventory. At that time, transport costs were highly affected by inflation, high interest rates, and the petrol crises. The deregulation in the first world has caused a new type of relationship among client, industry and transport organisations, and long term contracts were then established.

The post-deregulation era brought the internal logistics of the 80's, and a varied of market services, like third-party, just-in-time, electronic data interchange (EDI), and the widespread use of bar-code and personal computers. Reduction in both inventory investments and transport costs were provided by resource planning systems which were developed to match demand forecast with production schedule.

The 90's brought about the external integration among organisations, and highlighted the supply chain management importance and the customers satisfaction. As a consequence, electronic communication applications were widespread on a variety of new short names : ECR (Efficient Consumer Response), DSD (Direct Store Delivery), CRP (Continuous Replenishment Program), ERS (Evaluated Receipt Settlement), and VMI (Vendor Management Inventory). The ECR applies the machine learning possibilities to obtain client information for customising services (Alves, 1997). Electronic change of data and documentation among organisations / customers eliminates a great amount of secretarial work on commercial bills typing, and speed up negotiations. The CRP (Continuous Replenishment Program) allows the automatic replenishment of goods according to client's needs, while the ERS (Evaluated Receipt Settlement) provides all accountancy and cash register functions. Without intermediate distribution centres, direct sells to shops are provided by DSD (Direct Store Delivery), and with the support of VMI (Vendor Management Inventory) supplier can even process the client's stock management (Faé, 1997 b).

The supply chain management has carried the integration function concept out of the organisation, since it comprises the chain of participants from suppliers to customers. The organisation itself is part of the whole process, which needs the interaction and contribution of all components. Such an external integration has highlighted the importance of eletronic trade and the ECR (Efficient Consumer Response) techniques.



During the 70's, the development of simulation languages required specific professional training. Both the development of systems and the debugging of simulation models were very much time consuming. Such a problem were partially overcome by the widespread of PCs, which have become popular during the 80's. As a consequence, many simulation tools were available to any professional without specific training.

The usual question applied to simulation systems was "what if". Many scenarios could then be build up to deal with that problem. Nowadays, the 4th generation software drives the question to "how", what means that a problem is modelled and the software itself shows the best operation procedure to be pursued. Actually, most of the time and effort required on a simulation project is due to the result analysis, and less to the programming and debugging themselves (Norman, 1997).

Simulation tools can be applied to various logistics problems:

  • Material handling
    • Production planning and control - program to minimise the distribution time and to maximise the resources
    • New technologies - to measure the performance and the relation cost/benefit of a usual procedure compared to a system that uses information technology
    • Storage and distribution - to place central distribution locations and to define the best alternatives for storing finished products
    • Supply chain management - inside a firm among its various departments and also between a firm and its suppliers and clients
  • Lay out - new installation and expansion of the actual capacity



The Universidade Federal do Espirito Santo, associated with Brazilian Universities, is developing a research program called "Logistics and Simulation of Transport Corridors / Mercosul which aims to develop tools to analyse the performance of the brazilian transport network as concerns each corridor, in order to maximise the transport flow and minimise its costs. To deal with such a problem, simulation methods were found to be adequate both to evaluate the performance of the system and also provide the decision support concerning operational activities and investments (UFES-USP, 1996).

Two approaches were proposed to face the problem: (i) simulation of the network, and (ii) operation of the network. The simulation involves the development of a model based on multiple commodity flow techniques with the aims to evaluate the performance of the actual network to provide support for decisions on investment appraisal. The goal is to find a flexible tool which deals with various indices, eg. maximum flow, minimum costs, minimum distances, such that it can be used both for improvements in the actual network and also in the opening of new tracks. Regarding the operational side, the simulation tool can also be used for impact evaluation due to the application of new information technology. For each potential scenario drawn, the impacts over the transport system can be evaluated.

Multiple commodity flow occurs when various commodities (cars, cereal grains, minerals, electronic components), which can not be mixed up, are transported in a network with capacity restriction. The definition of maximum flow of multiple commodities can be described as a set of demand flows (one for each commodity) transported within the capacity limit given by the network. In such a case, the flow of each commodity is defined as the relation between the actual commodity flow and the commodity demand. When the demand of all commodities are attended, all of then have flow equal 1. When one of the commodities demand is not attended, than its flow is less than 1. The maximum of the multiple commodity problem is the network flow which assures the largest flow that is allowed for each commodity, provided that the total flow is kept constant. In other words, demand is equally attended in the network as concerns the flow of each commodity. Provided that the model input data (i) capacity limitations and (ii) demand flow for each commodity are given, one can obtain a network flow that attends sucha a demand. Scheduling problems can be solved by decomposing the network on parts and scheduling such small elements (Tsen, 1995).

Algorithms given by Bianchini (1989) and Even & Messerschmitt (1976) applied to the multi commodity flow problem allow the investigation of the following aspects :

  • does the network support the demand flow ?
  • will the network support the forecast demand ?
  • what will be the impact caused by expansion and improvement in the network ?
    • What are the effects due to political fare changes which intend to balance the network?
    • What will be effect of new terminals and facilities along the network ?



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Maria Inês Faé is Civil Engineer by Universidade Federal do Espírito Santo, Brasil, 1977. MSc in Transport, Escola de Engenharia de São Carlos, Universidade de São Paulo, in 1983. PhD in Transport, Leeds University, England, in 1993. Senior lecturer at Univesidade Federal do Espirito Santo, Brasil. Coordinator of a co-joint project with Universidade de São Paulo concerning logistics and simulation of transport corridors. Coordinator of the post-graduate course on intermodal transportation at Universidade Federal do Espirito Santo. Orientation of MSc students on Environmental Engineering.