Solving Resource-Constrained Project Scheduling Problems Using Hybrid Artificial Bee Colony with Differential Evolution

Abstract

Solving resource-constrained (RC) project scheduling problems is one the most important tasks in the project planning process. This study presents a new hybrid approach, named Artificial Bee Colony with Differential Evolution, to handle resource-constrained problems (ABCDE-RC). The proposed algorithm integrates crossover operations from differential evolution (DE) with original artificial bee colony (ABC) to balance exploration and exploitation phases of the optimization process. Furthermore, this study applies a serial method to reflect individual-vector priorities into the active schedule to calculate project duration. The ABCDE-RC algorithm is compared with benchmark algorithms considered using a real construction case study and a set of standard problem available in the literature. The experimental results demonstrate the efficiency and effectiveness of the proposed model. The ABCDE-RC is a promising alternative approach to handling resource-constrained project scheduling problems.