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Operators of the Two-Part Encoding Genetic Algorithm in Solving the Multiple Traveling Salesmen Problem

机译:求解多个旅行销售人员的两部分编码遗传算法的运营商

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The multiple traveling salesmen problem (mTSP) considers the $m$ salesmen to visit $n$ cities. This problem involves the assignment of the salesmen to some locations and we have to optimize the sequence within the route, so it is even harder than the traveling salesman problem (TSP) in nature. As a result, there are some algorithms used to solve the mTSP when the problem size is large. Particularly, genetic algorithm (GA) is quite famous in solving this problem while the problem size is large. When we compare the major existing encoding methods for mTSP, the best approach could be the two-part chromosome encoding due to its solution space is the smallest. The two parts are responsible for the sequence and the number of cities should be visited by each salesman. However, because the two-part chromosome technique is the recently proposed encoding method, the better combination of the crossover operators and mutation operators have not studied for this encoding method. As a result, this paper investigates the genetic operators could be used for this purpose by design-of-experiments (DOE). The appropriate genetic operators are suggested in this paper and it could be used to applied in the GA which employs the two-part chromosome encoding technique.
机译:该多旅行商问题(MTSP)认为$ M $推销员拜访$ n $的城市。这个问题涉及到推销员一些地方的分配,我们必须路线中的优化序列,所以这是更难比自然界中的旅行商问题(TSP)。其结果是,有用于解决MTSP当问题尺寸大一些算法。特别是,遗传算法(GA)是当问题规模大解决这个问题颇负盛名。当我们比较了中期战略计划现有的主要编码方法,最好的办法可能是由两部分组成染色体编码由于其解空间是最小的。这两个部分是负责的顺序和城市的数量应该由每个业务员参观。然而,由于两部分染色体技术是最近提出的编码方法,交叉运营商和变异算的更好的结合还没有研究对这种编码方法。其结果是,本文研究的遗传操作可通过设计的-实验(DOE)被用于此目的。合适的遗传算子本文提出了,它可以用于在采用两部分染色体编码技术的GA应用。

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