A differential evolution algorithm with local search for resource investment project scheduling problems

In this paper, we propose a differential evolution algorithm with local search to solve the resource investment project scheduling problems (RIPSPs), labeled as DELS-RIPSP. Project tardiness is not permitted during the process of optimization. DELS-RIPSP improves the population quality by changing existing chromosomes to those with better fitness using the local search operator in order to reduce resource cost. The performance of DELS-RIPSP is validated on 450 benchmark problems, including Mohring instances and ProGen instances with 10, 14 and 20 non-dummy activities. The percentages of optimal solutions under a fixed number of evaluations are reported. The experimental results illustrate the effectiveness of the proposed algorithm and its potential for solving RIPSPs.