Purpose: Network design of the supply chain is an important and strategic aspect of logistics management. In this paper, we address the network design problem specific to packaged gases (cylinder) supply chain. We propose an integrated framework that allows for the determination of the optimal facility locations, the filling plant production capacities, the inventory at plants and hubs, and the...

An incremental network model is introduced which is able to learn the important topological relations in a given set of input vectors by means of a simple Hebb-like learning rule. In contrast to previous approaches like the "neural gas" method of Martinetz and Schulten (1991, 1994), this model has no parameters which change over time and is able to continue learning, adding units and connection...

The growing neuron gas (GNG) algorithm is an excellent self-organization tool, which efficiently combines the graph and neural network techniques. The gas formation starts with two connected neurons and during the training both the neurons (nodes) and their connections are iteratively added.The most relevant advantage of this technology is that it forms the final graph structure considering the...

To comprehensively understand the characteristics of gas nanosensor between temperature and sensitivity, this paper has developed a Backward Propagation (BP) neural network based on Particle Swarm Optimization (PSO), which is applied to fitting the temperature-sensitivity characteristic of the SnO2 gas nanosensor mixed with benzene. The simulation results show the PSO can well optimize the stru...

Oil and gas pipelines are the infrastructure of national economic development. Deployment problem of wireless underground sensor networks (WUSN) for oil and gas pipeline systems is a fundamental problem. This paper firstly analyzed the wireless channel characteristics and energy consumption model in near-surface underground soil, and then studied the spatial structure of oil and gas pipelines a...

In this study, the energy consumption in the food and beverage industries of Iran was investigated. The energy consumption in this sector was modeled using artificial neural network (ANN), response surface methodology (RSM) and genetic algorithm (GA). First, the input data to the model were calculated according to the statistical source, balance-sheets and the method proposed in this paper. It ...

Sustainable supply chain has become an integral part of the corporate strategy. In this paper, a real case study of the natural gas supply chain has been investigated. Using concepts related to natural gas industry and the relations among the compo-nents of gas and oil wells, refineries, storage tanks, dispatching, transmission and distribution network, a seven-level supply chain has been intro...

In this paper, a new neural network model called the hierarchical overlapped neural gas (HONG) network is introduced and its performance on several datasets is described. In order to obtain improved classification accuracy, the HONG network partitions the input space by projecting the input data onto several different second layer neural gas networks. This duplication enables the HONG network t...

Hydrogen is of great significance for replacing fossil fuels and reducing carbon dioxide emissions. The application hydrogen mixing with natural gas in network transportation not only improves the utilization rate energy, but also reduces cost large-scale updating household or commercial appliance. This paper investigates necessity a device adding to existing pipelines industrial network. A thr...