A bio-inspired algorithm based on membrane computing and its application to gasoline blending scheduling
A bio-inspired algorithm based on membrane computing and its application to gasoline blending scheduling
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DOI：
10.1016/j.compchemeng.2010.01.008
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发表时间：
2011-02
期刊：
影响因子：
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通讯作者：
Jinhui Zhao;Ning Wang
中科院分区：
文献类型：
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作者：
Jinhui Zhao;Ning Wang
为了将膜计算作为一种全局优化技术应用于求解有约束和无约束问题，提出了一种基于膜计算的生物启发算法（BIAMC）. BIAMC中使用的膜结构是受高尔基体启发的膜网络。在接近最优解的过程中，包含试探解的对象在平行的相同膜中通过重写规则进化，并在准高尔基体膜中通过目标指示、转移和抽象的新规则合成。信息根据通信规则定义的方向传输。八个著名的无约束和约束函数用于性能测试。最后，将该算法应用于一个典型的汽油调合调度非线性优化问题。结果表明，该方法可以有效地找到最优或接近最优的解决方案。
For the purpose of applying membrane computing as a global optimization technique, a bio-inspired algorithm based on membrane computing (BIAMC) is proposed to solve both constrained and unconstrained problems. The membrane structure used in BIAMC is a network of membranes that is inspired by the Golgi apparatus. In the process of approaching to the optimum solution, the objects containing a tentative solution are evolved by the rewriting rule in the parallel identical membranes and synthesized by the novel rules of target indication, transition and abstraction in the membrane of quasi-Golgi. The information transfers according to directions defined by the communication rule. Eight well-known unconstrained and constrained functions are used for performance testing. Then we apply the proposed algorithm with two schemes to solving a typical nonlinear optimization of gasoline blending and scheduling problem. The results show that the proposed approach can find optimal or close-to-optimal solutions efficiently.