In this paper, a modified version of social group optimization (SGO) has been proposed i.e discreet social group optimization (DSGO), to find out the optimal path for travelling salesman problem (TSP), which is one of the well known NP-Hard problems. Its performance has been compared with Genetic Algorithm (GA) and Discrete Particle Swarm Optimization (DPSO) and the results found are competitive. It is observed that DSGO converges faster than DPSO and GA and also provides more optimal results for bigger size data.

中文翻译：

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使用离散型社会群体优化解决旅行商问题

本文提出了一种改进的社会群体优化（SGO）版本，即谨慎的社会群体优化（DSGO），以找出旅行商问题（TSP）的最佳路径，这是众所周知的NP-Hard之一问题。它的性能已与遗传算法（GA）和离散粒子群优化（DPSO）进行了比较，发现的结果具有竞争力。可以看出，DSGO的收敛速度比DPSO和GA快，并且对于更大的数据量，它还提供了更好的结果。