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A membrane-inspired algorithm with a memory mechanism for knapsack problems

机译:具有背包机制问题的具有记忆机制的膜启发算法

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membrane algorithms are a class of distributed and parallel algorithms inspired by the structure and behavior of living cells. Many attractive features of living cells have already been abstracted as operators to improve the performance of algorithms. In this work, inspired by the function of biological neuron cells storing information, we consider a memory mechanism by introducing memory modules into a membrane algorithm. The framework of the algorithm consists of two kinds of modules (computation modules and memory modules), both of which are arranged in a ring neighborhood topology. They can store and process information, and exchange information with each other. We test our method on a knapsack problem to demonstrate its feasibility and effectiveness. During the process of approaching the optimum solution, feasible solutions are evolved by rewriting rules in each module, and the information transfers according to directions defined by communication rules. Simulation results showed that the performance of membrane algorithms with memory cells is superior to that of algorithms without memory cells for solving a knapsack problem. Furthermore, the memory mechanism can prevent premature convergence and increase the possibility of finding a global solution.
机译:膜算法是一类受活细胞的结构和行为启发的分布式和并行算法。活细胞的许多吸引人的功能已经被抽象为运算符,以提高算法的性能。在这项工作中,受存储信息的生物神经元细胞功能的启发,我们通过将存储模块引入膜算法来考虑一种存储机制。该算法的框架由两种模块(计算模块和存储模块)组成,它们都以环形邻域拓扑排列。他们可以存储和处理信息,以及彼此交换信息。我们在背包问题上测试了我们的方法,以证明其可行性和有效性。在寻求最佳解决方案的过程中,通过重写每个模块中的规则来发展可行的解决方案,并且信息根据通信规则定义的方向进行传递。仿真结果表明,具有存储单元的膜算法在解决背包问题方面的性能优于不具有存储单元的膜算法。此外,存储机制可以防止过早收敛,并增加找到全局解决方案的可能性。

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