Title :
Random Assignment Method Based on Dynamic Constraint and Genetic Algorithm
Author :
Li, Fachao ; Jin, Chenxia ; Liu, Limin
Author_Institution :
Hebei Univ. of Sci. & Technol., Shijiazhuang
Abstract :
In this paper, by using the dynamic relationship between mathematical expectation and variance and the compound quantitative description of random variable, an instructive solution model for random assignment problem has been developed; combining the characteristic of assignment problem, give the concrete scheme based on genetic algrithm (denoted by B.DC(S)GA-RAM, for short); finally, consider its convergence using Markov chain theory, and analyze its performance through an example. All these indicate that, this solution model can effectively merge decision consciousness into the assignment process, posses interesting features of strong interpretability, easy operation and higher computation efficiency, so it can be widely used in many fields.
Keywords :
Markov processes; constraint theory; genetic algorithms; random processes; Markov chain theory; assignment problem; compound quantitative description; dynamic constraint; genetic algorithm; mathematical expectation; random assignment method; Analysis of variance; Concrete; Constraint theory; Fluctuations; Genetic algorithms; Marketing and sales; Mathematical model; Performance analysis; Random variables; Uncertainty;
Conference_Titel :
Innovative Computing, Information and Control, 2007. ICICIC '07. Second International Conference on
Conference_Location :
Kumamoto
Print_ISBN :
0-7695-2882-1
DOI :
10.1109/ICICIC.2007.472