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In this paper it is developed a location model for the infrastructures dedicated to non-motorized movements by bike in Oradea city, using ArcGIS geographic and information system [3]. They are taken into consideration the movements made by the target people – alternating movements (from home to school) and optional movements (made for recreation), the densities in residential areas, the type of the city arteries and the mobility need of the target people (in this case – young people aged between 15 and 25) in order to design two structures of the transport infrastructure networks (one for the alternating movements and the other for the optional movements), structures which will be realized on the actual frame of the existing transport infrastructure in Oradea city. Using Dijkstra algorithm, the minimal routes for the movements related to the alternating mobility, but also for the movements specific to the optional mobility are determined. Further on the most used arteries in the two structures of urban infrastructure networks are determined. The paper suggests as a solution the structure of the network for the non-motorized movements and also those arteries that must be used for its development, that guarantee gains for the target people (time), for the main operators who exploit the motorized systems, for the local budget of the local municipalities (less funds to sustain the public services) and especially for the environment and people’s health (attenuation of noxious and phonic pollution, reduction of the accidents’ number and health improvement).

Warehousing enables the consolidation of shipments to clients by assembling full truck loads from goods stored in warehouse or distribution center. Storage can be efficiently replenished by ordering full truck loads from suppliers. In order to reduce freight storage and handling costs from distribution centers, cross-docking technique represents a logistic solution which is more and more used. Thus, the optimization of simultaneous unloading/loading operations constitutes an important issue for the distribution center owner/administrator. This paper presents a model based on genetic algorithms optimization techniques for solving the problem of unloading/loading ramps allocation. The efficiency of a cross-docking center is conditioned practically by finding an allocation and an optimal arrangement of ramps. This implies the allocation of destinations to unloading/loading ramps of distribution centers to minimize the total distance performed by the the cargo handling equipment. The case study presents a cross-docking platform with single handling equipment which is assigned to 10 unloading/loading ramps. By applying the solution of the ramp allocation generated through simulation, the total distance performed by the handling equipment is reduced which means lower handling cost for the distribution center owner/administrator.

One of the most frustrating problems when dealing with risks it’s that they come in so many different forms. They can appear at any point in a port logistic system, they can interrupt the supply of raw materials or products, they can cause demand fluctuations (peak or collapse), inventory problems (lack or crowding), dispatch delay. Risks can range on a scale from small delay to a natural disaster, from short term to a permanent damage, with effects localized on a part of a supply chain or affecting the whole chain activity. The risk management allows port administration to take appropriate measures to reduce the consequences of a risk, to provide a good reliability of the logistic system or to design a resilient one. The paper investigates the major risks in port logistics and adequate measures to minimizing their effects. A risk management tree is set-up. Using computer simulation modelling, a case study investigates the port logistic system behaviour under different risk scenarios and evaluates the reliability of the system and its resilience. The operation capacity for different port logistics sub-system is assessed taking into consideration the required operating standards and the measures of performance (e.g. waiting time for vessels and transport vehicles, storage area and time for commodities) of the logistic system are computed.