Integrate the Hungarian Method and Genetic Algorithm to Solve the Shortest Distance Problem

2012 ◽  
Author(s):  
Chin-Jung Huang
Keyword(s):  
Genetic Algorithm ◽  
Hungarian Method ◽  
Shortest Distance ◽  
Distance Problem

Information Bounds Are Weak in the Shortest Distance Problem

1980 ◽  
Vol 27 (3) ◽  
pp. 428-444 ◽  
Author(s):  
Ronald L. Graham ◽  
Andrew C. Yao ◽  
F. Frances Yao
Keyword(s):  
Shortest Distance ◽  
Distance Problem

ON THE COMPUTATION OF THE RELATIVE ENTROPY OF PROBABILISTIC AUTOMATA

2008 ◽  
Vol 19 (01) ◽  
pp. 219-242 ◽  
Author(s):  
CORINNA CORTES ◽  
MEHRYAR MOHRI ◽  
ASHISH RASTOGI ◽  
MICHAEL RILEY
Keyword(s):  
Machine Learning ◽  
Relative Entropy ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Probabilistic Automaton ◽  
Probabilistic Automata ◽  
Gaussian Kernels ◽  
Shortest Distance ◽  
Distance Problem ◽  
Number Of Publications

We present an exhaustive analysis of the problem of computing the relative entropy of two probabilistic automata. We show that the problem of computing the relative entropy of unambiguous probabilistic automata can be formulated as a shortest-distance problem over an appropriate semiring, give efficient exact and approximate algorithms for its computation in that case, and report the results of experiments demonstrating the practicality of our algorithms for very large weighted automata. We also prove that the computation of the relative entropy of arbitrary probabilistic automata is PSPACE-complete. The relative entropy is used in a variety of machine learning algorithms and applications to measure the discrepancy of two distributions. We examine the use of the symmetrized relative entropy in machine learning algorithms and show that, contrarily to what is suggested by a number of publications in that domain, the symmetrized relative entropy is neither positive definite symmetric nor negative definite symmetric, which limits its use and application in kernel methods. In particular, the convergence of training for learning algorithms is not guaranteed when the symmetrized relative entropy is used directly as a kernel, or as the operand of an exponential as in the case of Gaussian Kernels. Finally, we show that our algorithm for the computation of the entropy of an unambiguous probabilistic automaton can be generalized to the computation of the norm of an unambiguous probabilistic automaton by using a monoid morphism. In particular, this yields efficient algorithms for the computation of the Lp-norm of a probabilistic automaton.

scholarly journals A New Algorithm for Distributed Control Problem with Shortest-Distance Constraints

2016 ◽  
Vol 2016 ◽  
pp. 1-6
Author(s):  
Yu Zhou ◽  
Wenfeng Zheng ◽  
Zhixi Shen
Keyword(s):  
Distributed Control ◽  
Multiagent Systems ◽  
Local Information ◽  
Common Point ◽  
Consensus Algorithm ◽  
Time Dynamics ◽  
Shortest Distance ◽  
Distributed Control Problem ◽  
Distance Problem ◽  
Theoretical Results

This paper investigates the distributed shortest-distance problem of multiagent systems where agents satisfy the same continuous-time dynamics. The objective of multiagent systems is to find a common point for all agents to minimize the sum of the distances from each agent to its corresponding convex region. A distributed consensus algorithm is proposed based on local information. A sufficient condition also is given to guarantee the consensus. The simulation example shows that the distributed shortest-distance consensus algorithm is effective for our theoretical results.

The Research of Vehicle Routing Problem With Time Window for Changsha Yunda Express in Kaifu District

2013 ◽  
Vol 336-338 ◽  
pp. 2525-2528
Author(s):  
Zhong Liu
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Distribution Center ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Routing Problem ◽  
Service Levels ◽  
Shortest Distance

For express companies' distribution center, optimizing the vehicle routing can improve service levels and reduce logistics costs. This paper combines the present vehicle routing situation of Chang Sha Yunda Express in KaiFu area with the specific circumstances to analyze. A model of the vehicle routing problem with time window for the shortest distance was built and then use genetic algorithm to solve the problem. Its application showed that the method can effectively solve the current vehicle routing problems.

O(1) QUERY TIME ALGORITHM FOR ALL PAIRS SHORTEST DISTANCES ON INTERVAL GRAPHS

1999 ◽  
Vol 10 (04) ◽  
pp. 465-472 ◽  
Author(s):  
ALAN P. SPRAGUE ◽  
TADAO TAKAOKA
Keyword(s):  
Time Algorithm ◽  
Interval Graph ◽  
Query Time ◽  
Circular Arc ◽  
Interval Model ◽  
Erew Pram ◽  
Pram Model ◽  
Shortest Distance ◽  
Distance Problem ◽  
Circular Arc Graphs

We present an algorithm for the All Pairs Shortest Distance problem on an interval graph on n vertices: after O(n) preprocessing time, the algorithm can deliver a response to a distance query in O(1) time. The method used here is simpler than the method of Chen et al. [4], which has the same preprocessing and query time. It is assumed that an interval model for the graph is given, and ends of intervals are already sorted by coordinate. The preprocessing algorithm can be executed in the EREW PRAM model in O( log n) time, using n/ log n processors. These algorithms (sequential and parallel) may be extended to circular arc graphs, with the same time and processor bounds.

SOLVING A FUEL DISTRIBUTION PROBLEM USING GENETIC ALGORITHM: A TRAVELING SALESMANPROBLEMAPPROACH

2018 ◽  
Vol 12 (Number 1) ◽  
pp. 51-55
Author(s):  
Rosshairy Abd Rahman ◽  
Nurul Ezatty Mokhtar ◽  
Ummu Latifah Bahrom
Keyword(s):  
Genetic Algorithm ◽  
Traveling Salesman ◽  
Hill Climbing ◽  
Distribution Problem ◽  
High Demand ◽  
Fuel Distribution ◽  
Petrol Station ◽  
Shortest Distance ◽  
Distribution Process ◽  
The Cost

Petrol or fuel is the product that people use daily and have a high demand. Therefore, the delivery of petrol from origin to each petrol station is done daily. This distribution process concerns the management as they have to minimize the cost while maximizing the profit. Hence, this paper aims to develop a model that is able to determine the shortest path for delivery these petrol in one company in Selangor. The problem is solved using Traveling Salesman Problem (TSP) approach, where the data were collected using Google Maps application. The shortest distance was attained using Genetic Algorithm (GA) technique. The solution obtained from GA was then compared with Hill Climbing technique. The results shows that GA produces better solution and could cut the distance up to 23 km. The finding of this research would help the company to reduce the cost of distributing refined fuel around Selangor.

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