Combinatorial designs provide an interesting source of optimization problems. Among them, permutation codes are particularly interesting given their applications in powerline communications, flash memories, and block ciphers. This paper addresses the design of permutation codes by evolutionary algorithms (EA) by developing an iterative approach. Starting from a single random permutation, new permutations satisfying the minimum distance constraint are incrementally added to the code by using a permutation-based EA. We investigate our approach against four different fitness functions targeting the minimum distance requirement at different levels of detail and with two different policies concerning code expansion and pruning. We compare the results achieved by our EA approach to those of a simple random search, remarking that neither method scales well with the problem size.
翻译:组合设计提供了最优化问题的有趣来源。 其中, 变异代码特别有趣, 因为它们在电线通信、 闪存和块密码中的应用。 本文通过开发迭接法处理进化算法( EA) 的变异代码设计。 从单一随机变异学开始, 能够满足最低距离限制的新变异学会通过使用以变异为基础的EA逐渐添加到代码中。 我们调查了我们针对四种不同的健身功能的方法, 分别针对不同详细程度的最低距离要求, 以及两个关于代码扩展和剪裁的不同政策。 我们比较了我们的变异算法( EA) 所取得的成果和简单随机搜索的结果, 指出这两种方法都与问题大小不相称。