Resource-constrained Project Scheduling Based On Ant Colony Algorithm

In the past few years,the high-speed train system in China has been developing fast.Meanwhile,the manufacturers of high-speed train are facing great challenges as well as opportunities.There is enormous market demand in both domestic and international market on one hand,and on the other hand,the competition has become more and more intense.The complex market situation has made the manufacturers facing a higher challenge.Producing time,producing cost,project management skills are all affecting the competitive power of the corporation besides technology and quality.Recently,more and more new types of high-speed trains are brought to the market,which means the pilot project of high-speed train becomes much more regular than before.However,the traditional way of schedule the procedures is based on experience only.That could lead to problems,as it is lack of scientific methods.In this article,we study the pilot project of the bogie of high-speed train and try to find a more scientific way to manage the arrangement of each single procedure.The pilot project of the bogie of high-speed train is classified as resource-restrained project.We try to figure out the character of pilot project of the bogie of high-speed train by learning the problems of resource-retrained projects.Particularly,we study the commonly used solutions and find the most suitable solution-ant colony algorithm(ACA).We Then,we look for the best solution according to the instructed target and regulation with ACA.Further,we study the project resource and characters of ACA so that we can build the theoretical foundation of the research including the critical steps of pheromone emission,pheromone updating and ants generation changing.For the pilot project of the high-speed train,we drew the work breakdown structure and the project network diagram and find out a solution by making a simulation with Excel VBA.We analyzed the result and optimized the production line structure.The total time of one big process now in the example has decreased to 94.5% of before,and the process balance rate has increased by 261% with the optimization.With all these effort,we have built a practical method of simulating,solving and optimizing the similar problem.