改进的膜计算仿生优化算法及在汽油调和中的应用

为提高膜计算仿生优化算法在求解流程工业复杂优化问题的计算性能,提出一种改进的膜计算仿生优化算法。该算法采用一个新的不确定性提取规则取代改进前的提取规则。4个有约束标准测试函数被用于检验该算法的计算性能,计算结果及对比显示了改进算法在鲁棒性和效率等方面优于改进前算法。改进算法应用于汽油调和优化问题,更高利润的配方及算法的计算效率证实了改进算法的优越性和实用性。

Modified bio-inspired algorithm based on membrane computing and application in gasoline blending

Aiming at improving the computational performance of bio-inspired algorithm based on membrane computing(BIAMC)in solving complex optimization problems in process manufacturing,a modified bio-inspired algorithm based on membrane computing(MBIAMC)is proposed.In MBIAMC,a new indeterministic abstraction rule is applied which substitutes the abstraction rule of BIAMC,and the algorithmic framework and other rules are inherited from BIAMC.For solving constrained optimization problems,the quadratic penalty function method is introduced in MBIAMC.Four constrained benchmark functions are used to evaluate computational performance of MBIAMC.The results and comparison with other two algorithms handling constraints problems reveal that MBIAMC is efficiency and superiority to BIAMC in accuracy and robustness.As a case study,MBIAMC is used to solve gasoline blending optimization problem,the better recipes and its lower computational cost validate its higher efficiency and more practicability.