An Inverse Optimal Value Approach for Synchronously Optimizing Activity Durations and Worker Assignments with a Project Ideal Cost

Most companies survive the pain of cost and schedule overruns because inaccurate project activity time settings. In order to deliver a with target on schedule, this research proposes an inverse optimal value approach optimize durations corresponding worker assignments synchronously make infinitely close ideal cost. The leader model reflects orientation adjustability durations, follower complexity sequence, critical path completion time, pressure, skill matching, energy consumption, other costs. Through upper-level lower-level feedback interaction it is possible With considerations mathematical characteristics bi-level programming, nonlinearity, NP hard, MAX functions, improved genetic algorithm combining adaptive artificial fish swarms designed. From comparison results random examples actual example, error rate acceptable. Numerical experiments show that can without delay optimization method more in line idea management, help managers achieve purpose control.