A GENETIC ALGORITHM APPROACH FOR OPTIMIZING CHEMICAL TOWER CONSTRUCTION PROJECT SCHEDULING WITH DYNAMIC RESOURCES CONSTRAINTS

In this paper we investigate a model of dynamic resource constrained project scheduling problem (DRCPSP) for a chemical tower construction project. The objective function is to minimize makespan. The characteristic of resources constraint in a DRCPSP is unlikely the resource constrained project scheduling problem (RCPSP) in the literature. The resources required are not only independent resources but also dynamic resources which depend on jobs processing sequence (JPS). A modified genetic algorithm with the auto-shift method (GAASM) is proposed to search for the optimal solution for the objective function. A real-life example is presented to illustrate that the GAASM algorithm is feasible. Simulation experiments of eight problems with 240 runs show that the GAASM outperforms the conventional GA based method (GABM), and eight groups with a total of 240 problems show that the GAASM can improve and reduce the makespan average 5.09%－14.60% compared with two heuristic company plan (CP) rules