Balancing Global Project Resources Utilising a Genetic Algorithm Approach with Stochastic Resource Assignments
Globalisation in large engineering, procurement and construction companies has lead in many cases to the establishment of a number of global centres for activities such as process design, detail design, procurement and fabrication. A company with a number of such resources then faces the problem of maintaining a high percentage utilisation in each of these resource locations, multiple projects need to be processed through each of these offices and which project is handled by which office is generally more reliant on available capacity than geography, particularly in the case of engineering centres. This paper considers this problem as an extension of the well studied Resource Constrained Project Scheduling Problem (RCPSP) and utilises a modified form of our existing genetic algorithm to optimise the utilisation of multiple resource locations when scheduling multiple projects. The unique aspect of this genetic algorithm implementation is its use of stochastic resource assignments to simulate the assignment of certain of the project activities to different global facilities. The stochastic resource assignment is processed as an extension to the main chromosome and is therefore optimised along with the scheduling sequence.
Kai Cheng, Yingxue Yao and Liang Zhou
J. Lancaster and K. Cheng, "Balancing Global Project Resources Utilising a Genetic Algorithm Approach with Stochastic Resource Assignments", Applied Mechanics and Materials, Vols. 10-12, pp. 67-72, 2008