Abstract
One subcategory of project scheduling is the resource constrained project scheduling problem (RCPSP). The present study proposes a differential evolution algorithm for solving the RCPSP making a small change in the method to comply with the model. The RCPSP is intended to program a group of activities of minimal duration while considering precedence and resource constraints. The present study introduces a differential evolution algorithm and local search was added to improve the performance of the algorithm. The problems were then solved to evaluate the performance of the algorithm and the results are compared with genetic algorithm. Computational results confirm that the differential evolution algorithm performs better than genetic algorithm.
Highlights
Scheduling of projects can be implemented for optimization planning, consensus planning, milestone schedules, and outage schedules (Klimek, 2011)
The present study has examined the resource investment problem using a Differential evolution (DE) algorithm
It was demonstrated that DE performed differently for different problems
Summary
Scheduling of projects can be implemented for optimization planning, consensus planning, milestone schedules, and outage schedules (Klimek, 2011). Arjmand and Najafi (2015) solved a multi-mode bi-objective resource investment problem using two modified meta-heuristic algorithms they called NSGA-II and MOPSO. They compared the algorithms using the MADM approach called TOPSIS. Koulinas et al (2014) presented particle swarm optimization for solving RCPSP based on a hyper-heuristic algorithm. The basis of the algorithm is the use of distance and direction information from the current population to carry out search operations (Amiri & Barbin, 2015) It appears that DE has the ability to solve complex RCPSP problems. The present study developed a DE for RIP with a single mode resource constrained project.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
