Smart city Networks: Through the Internet of Things is composed of research
results, analyses, and ideas, which focus on a diversity of interconnected factors
relating with urbanization, its “smartness,” and overarching “internet of things
(IoT).” The latter refers to interconnected objects and devices – through compu-
tational operations – which can receive signals and actuate systems.
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
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This program is using Genetic Algorithm to solve the Travlling
Salesman Problem. It gives the best path route within a specified
time.
usage: java Evolver <seconds> <city file> <config file>
Author: Liu Yang
Implemented BFS, DFS and A*
To compile this project, use the following command:
g++ -o search main.cpp
Then you can run it:
./search
The input is loaded from a input file in.txt
Here is the format of the input file:
The first line of the input file shoud contain two chars indicate the source and destination city for breadth first and depth first algorithm.
The second line of input file shoud be an integer m indicate the number of connections for the map.
Following m lines describe the map, each line represents to one connection in this form: dist city1 city2, which means there is a connection between city1 and city2 with the distance dist.
The following input are for A*
The following line contains two chars indicate the source and destination city for A* algorithm.
Then there is an integer h indicate the number of heuristic.
The following h lines is in the form: city dist which means the straight-line distance from the city to B is dist.
this m file can Find a (near) optimal solution to the Traveling Salesman Problem (TSP) by setting up a Genetic Algorithm (GA) to search for the shortest path (least distance needed to travel to each city exactly once)
Notes:
1. Input error checking included
2. Inputs can be specified in any order, so long as the parameter pairs are specified as a parameter , value
