Abstract
Identifying and minimising the risks associated with time, and cost factors in construction projects are the main challenges for all parties involved. The objective of project management is to complete the scope of work on time, within budget and deliver a quality product in a safe fashion to maximise overall project success. This research presents a new hybrid multiple objective evolutionary algorithm based on hybridisation of Artificial Bee Colony (ABC) and differential evolution to facilitate time-cost-risk trade-off problems (MOABCDE-TCR). The proposed algorithm integrates core operations from Differential Evolution (DE) into the original ABC in order to enhance the exploration and exploitation capacity of the optimisation process. A numerical construction project case study demonstrates the ability of MOABCDE-generated non-dominated solutions to optimise TCR problem. Comparisons between the MOABCDE and currently widely used multiple objective algorithms verify the efficiency and effectiveness of the developed algorithm.
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