Title :
A neural network model for resource scheduling optimization
Author :
Fang, Xi ; Chen, Jing
Author_Institution :
Sch. of Water Conservancy & Hydropower Eng., Hohai Univ., Nanjing, China
Abstract :
Any change in resource planning may lead to change in project duration and resources cost which will impact the total cost of the project when risk factors are taken into account. A neural network model for resource scheduling to minimize the total cost of a project was proposed to improve the situation and Morte Carlo simulation and genetic algorithm were used to solve it. A case study based on the Neural Network model shows the optimization model is better than the Critical Path Method (CPM) network model.
Keywords :
Monte Carlo methods; critical path analysis; genetic algorithms; neural nets; resource allocation; scheduling; CPM; Morte Carlo simulation; critical path method; genetic algorithm; neural network model; optimization model; resource planning; resource scheduling optimization; Cost function; Electronic mail; Equations; Genetic algorithms; Hydroelectric power generation; Neural networks; Optimization methods; Random variables; Water conservation; Water resources; network programming; neural network; resource planning;
Conference_Titel :
Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5263-7
Electronic_ISBN :
978-1-4244-5265-1
DOI :
10.1109/ICIME.2010.5477602
