Infrastructure Planning Problems in Small and Medium Towns

1993 ◽  
Author(s):  
Subbarayan Prasanna
2017 ◽  
Vol 35 (7) ◽  
pp. 1285-1303 ◽  
Author(s):  
Shirin Malekpour ◽  
Rebekah R Brown ◽  
Fjalar J de Haan

The vision of sustainable development remains difficult to realize in practice. Processes of strategic planning for public infrastructure represent a major challenge, as, in many cases, they return unsustainable investment solutions. Research offers certain planning methodologies to improve the prospects of sustainable investments. However, very little is understood about how planning processes are undertaken in practice, and what problems in the procedural aspects of planning – termed “planning disruptions” in this paper – lead to deviations from the vision of sustainable development in infrastructure investments. This study scrutinizes the current scope of planning methodologies through the empirical case of a water supply augmentation in Melbourne, Australia. We derive a typology of planning disruptions which offers initial ingredients for a diagnostic tool to explore planning problems in the context of sustainable development. We also suggest making the current scope of planning methodologies more robust, by developing interventions that explicate and prepare for potential disruptions.


Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7833
Author(s):  
Sanchari Deb

As a result of environmental pollution and the ever-growing demand for energy, there has been a shift from conventional vehicles towards electric vehicles (EVs). Public acceptance of EVs and their large-scale deployment raises requires a fully operational charging infrastructure. Charging infrastructure planning is an intricate process involving various activities, such as charging station placement, charging demand prediction, and charging scheduling. This planning process involves interactions between power distribution and the road network. The advent of machine learning has made data-driven approaches a viable means for solving charging infrastructure planning problems. Consequently, researchers have started using machine learning techniques to solve the aforementioned problems associated with charging infrastructure planning. This work aims to provide a comprehensive review of the machine learning applications used to solve charging infrastructure planning problems. Furthermore, three case studies on charging station placement and charging demand prediction are presented. This paper is an extension of: Deb, S. (2021, June). Machine Learning for Solving Charging Infrastructure Planning: A Comprehensive Review. In the 2021 5th International Conference on Smart Grid and Smart Cities (ICSGSC) (pp. 16–22). IEEE. I would like to confirm that the paper has been extended by more than 50%.


A non-standard approach to solving the activation planning problems of the standardized products in a multinomenclature workshop is considered. This approach is caused by writing control programs and developing new information systems without changing previously developed workstations, which were created by using an outdated programming languages, in particular Clipper applications. The concept of creating a single information space — a set of databases and software tools integrated at the software level is proposed. Keywords standardized product; normal; software; web interface; single window; automatic work place; production task; shift task; order-shift report; control and registration card


1981 ◽  
Vol 11 (4) ◽  
pp. 315-323 ◽  
Author(s):  
Mike Moore ◽  
Woodrow Jones

2016 ◽  
Author(s):  
C. Heuer ◽  
C. Norris ◽  
J. Chwang

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