The Application Research Of Bionic Intelligent Algorithm In The Resource-constrained Project Scheduling Problem

Since project management theory has evolved with developments in socio-economics, fields relating to project management become more and more extensive, and the depth of problem researching on project management increases day by day. Project scheduling and planning are important components of project management, so the research about project scheduling has a significant impact on developing theory and enhancing the level of project management. Resource Constrained Project Scheduling Problem considers how to arrange activities’ start date and finish date reasonablely in project to ensure the project’s goal will be accomplished with the condition of resource-constrained and timingconstrained.Resource Constrained Project Scheduling Problem is already a certified NP-hard problem, meaning it is impossible to solve it via traditional methods, and bionic intelligent algorithm has a unique advantage on RCPSP, so this paper uses Bacterial Foraging Optimization algorithm on behalf of emerging bionic intelligent algorithm to solve RCPSP.In this paper, researching work includes mainly following content: 1) summarized the research status on RCPSP at home and abroad and made a literature review; 2) educing RCPSP from enterprise’s actual demand on project scheduling research and expounding theory and knowledge related to RCPSP systematicly; 3) introduced the basic principle and algorithm’s process of BFO; contraposing BFO’s defect in solving problem, educed the thought of PSO and cloud model, proposed adaptive hybrid bacterial foraging optimization algorithm based on cloud theory and took the aigorithm’s performance for a test to verify feasibility and effectiveness of CAHBFO; 4) using CAHBFO to solve classical RCPSP, proved that CAHBFO could solve RCPSP effectively via analog simulation in matlab; 5) made a scheduling management system of resource constrained project in matlab; and this system could optimization desigh different scale resource constrained project efficiently and gave both the optimal solution and the best scheduling shceme finally, having a good practical application value.The research result of this paper, not only extends the academic field of RCPSP, but also provides practical guidance for project managers coping with practical problem. Simultaneously, make a successful applications on RCPSP with BFO, extending the application field of BFO and also providing an entirely a new perspective and approach for seeking answers of combinatorial optimization problem like RCPSP.