The world population is continuously growing and reached a significant evolution of
the society, where the number of people living in Cities surpassed the number of people
in rural areas.
The status quo of digital Cities is analysed in detail, using six different
perspectives:
1. Social interaction
2. Safety
3. Data management and analytics
4. Mobility
5. Consumer Lifestyle
6. Crowd-based services
The concept of smart Cities emerged few years ago as a new vision for urban
development that aims to integrate multiple information and communication
technology (ICT) solutions in a secure fashion to manage a city’s assets. Modern ICT
infrastructure and e-services should fuel sustainable growth and quality of life,
enabled by a wise and participative management of natural resources to be ensured
by citizens and government. The need to build smart Cities became a requirement that
relies on urban development that should take charge of the new infrastructures for
smart Cities (broadband infrastructures, wireless sensor networks, Internet-based
networked applications, open data and open platforms) and provide various smart
services and enablers in various domains including healthcare, energy, education,
environmental management, transportation, mobility and public safety.
We review the current applications of photonic technologies to Smart Cities. Inspired
by the future needs of Smart Cities, we then propose potential applications of advanced
photonic technologies. We find that photonics already has a major impact on Smart
Cities, in terms of smart lighting, sensing, and communication technologies. We further
find that advanced photonic technologies could lead to vastly improved infrastructure,
such as smart water‐supply systems. We conclude by proposing directions for future
research that will have the greatest impact on realizing Smart City initiatives.
物流分析工具包。Facility location: Continuous minisum facility location, alternate location-allocation (ALA) procedure, discrete uncapacitated facility location
Vehicle routing: VRP, VRP with time windows, traveling salesman problem (TSP)
Networks: Shortest path, min cost network flow, minimum spanning tree problems
Geocoding: U.S. city or ZIP code to longitude and latitude, longitude and latitude to nearest city, Mercator projection plotting
Layout: Steepest descent pairwise interchange (SDPI) heuristic for QAP
Material handling: Equipment selection
General purpose: Linear programming using the revised simplex method, mixed-integer linear programming (MILP) branch and bound procedure
Data: U.S. Cities with populations of at least 10,000, U.S. highway network (Oak Ridge National Highway Network), U.S. 3- and 5-digit ZIP codes
A program to demonstrate the optimization process of ant colony optimization for the traveling saleman problem (TSP). The Cities are shown as red circles, the pheromone on the connections between them (fully connected graph) by gray lines. The darker the grey, the more pheromone is currently on the edge. During the optimization, the currently best found tour is drawn in red. To run the optimization, first create a random TSP, then create an ant colony, and finally run the optimization.
Traveling Salesman Problem (TSP) has been an interesting problem for a long
time in classical optimization techniques which are based on linear and nonlinear
programming. TSP can be described as follows: Given a number of Cities to visit
and their distances from all other Cities know, an optimal travel route has to be
found so that each city is visited one and only once with the least possible distance
traveled. This is a simple problem with handful of Cities but becomes complicated
as the number increases.
