A new weighted mixed integer nonlinear model and FPND solution algorithm for RCPSP with multi-route work packages under fuzzy uncertainty

Abstract

Multiple routes of networks in fuzzy environments are essential issues in the project scheduling problems (PSPs) with resource constraints, fuzzy RCPSP-MR. Route assignment to flexible work package defined in a project activity network indicates more complexities in front of canonical PSP. Also, in the last few decades, considering uncertainties’ concepts in project schedules have been essential and attracted the attention of researchers and project managers. Therefore, in this article, a new weighted mathematical model is presented under uncertainty conditions, and a new hybrid fuzzy approach is provided via two fuzzy primary methods. Then, a new four-part non-distinct (FPND) approach is proposed based on PSO, binary particle swarm optimization (BPSO) and genetic algorithm (GA) to minimize project end cost. In this approach as the first part and to generate high-quality primary routes for flexible work package, six different rules are investigated, and the appropriate route is chosen. In the second part, initial solutions are generated via PSO. Then, in the third part, initial solutions are improved based on GA. Finally, in the last part, assigned routes are improved with binary PSO. To appraise the effectiveness of the presented approach, influential parameters are tuned by Taguchi method. Finally, to evaluate the performance of FPND, 70 numerical examples are designed in different dimensions, and results are compared with other well-known algorithms.