Time-Cost-Quality trade off in Critical Chain Method with multi mode activities by Multi Objective Particle Swarm Optimization

Believing in the fact that an activity can be performed through several methods or states, or that there may be several executive states for activities with different numbers of resources in real conditions, the scheduling obtained from different methods with different combinations of time, resources, and quality need to be evaluated and optimized. These are referred to as project scheduling problems with multistate resources. On the other hand, application of the theory of constraints to project management has led to the development of a novel approach in project planning and control known as the critical chain. The present paper seeks to use the critical chain technique and simultaneous time-cost-quality trade off. In this study, the multi-objective problem of time-cost-quality trade off has been solved using the high capability of the multi-objective particle swarm algorithm in optimization and the critical chain technique, so that the most appropriate sequence and executive state of activities is found such that time, cost, and quality are optimized and close to reality. The optimization algorithm programming was coded in the MATLAB software, and the target results were extracted. For evaluation of the proposed model, two case studies with 7 and 18 activities have been solved. Furthermore, a project with 60 activities where the time-cost-quality trade off had been established were used for validation of the proposed algorithm, and new results were extracted. The results demonstrated that the developed algorithm has had correct, proper performance, in such a way that it is capable of generating several Pareto solutions with different time, cost, and quality values. Furthermore, the results have been reported separately based on the best time, cost, and quality, which makes it possible for the project managers to select the better solutions given their priorities in the project.