Dynamic and random differential evolution solving constrained optimisation problems

作者：Zhang Qing; Zeng Sanyou^*; Li Changhe

来源：International Journal of Computing Science and Mathematics, 2014, 5(2): 137-150.

DOI：10.1504/IJCSM.2014.064055

• Bench-mark problems
• Constrained optimisation problems
• Constraint handling
• Differential Evolution
• Dynamic optimisation
• Optimisations
• Scaling factors
• State-of-the-art algorithms

A dynamic and random differential evolution (DRDE) is designed in this paper to solve constrained optimisation problems (COPs). The dynamic means that the COP is transformed into a dynamic constrained optimisation problem (DCOP), then a DRDE is designed to solve the DCOP for solving the original COP. The key issue is to maintain a feasible population since a feasible population would vanish the difficulty in constraint handling. A deliberate setting of the environment can achieve the maintenance as much as possible. The 'random' in the DRDE means that the scaling factor of the DDE is randomly created in a range to increase search domain so as to enhance the performance of the DRDE. The DRDE is tested by a kit of widely used constraint benchmark problems. The experimental results suggest it outperforms or performs similarly to other state-of-the-art algorithms referred to in this paper.

• 出版日期2014