Institutul de Matematică şi Informatică "Vladimir Andrunachievici"
Universitatea de Stat din MoldovaRO EN
Solving transportation problems with concave cost functions using genetic algorithms
Authors: Tatiana Pașa
Keywords: genetic algorithm, population, minimum cost flow, non-linear transport problem, large-scale problem, concave function.
– 0.11 Mb
Keywords: genetic algorithm, population, minimum cost flow, non-linear transport problem, large-scale problem, concave function.
Abstract
In this paper we propose a genetic algorithm for solving the non-linear transportation problem on a network with concave cost functions and the restriction that the flow must pass through all arcs of the network. We show that the algorithm can be used in solving %{\color{red}large-scale} large-scale problems. We prove that the complexity of a single iteration of the algorithm is $O(nm)$ and converges to an $\epsilon$-optimum solution. We also present some implementation and testing examples of the algorithm using Wolfram Mathematica.Moldova State University
60 A. Mateevici, MD-2009, Chisinau
Republic of Moldova
E-mail:
60 A. Mateevici, MD-2009, Chisinau
Republic of Moldova
E-mail:
Fulltext
– 0.11 Mb
Contents
- Hospital-Scale Chest X-Ray Database Visualization Using RAWGraph Technique
- Solving transportation problems with concave cost functions using genetic algorithms
- Total k-rainbow domination subdivision number in graphs
- Chromatic Spectrum of Ks-WORM Colorings of Kn*
- On the Computational Complexity of Optimization Convex Covering Problems of Graphs
- On α-spectral theory of a directed k-uniform hypergraph
- C. Gaindric - National Prize Laureate of Moldova
