The single seekers society (SSS) algorithm is a recently developed meta-heuristic algorithm for solving complex continuous optimization problems. The aim of this paper is to adapt the SSS algorithm to handle combinatorial optimization problems. As the original SSS algorithm does, the combinatorial SSS algorithm also brings several single-solution based search algorithms together while making them to communicate through an information mechanism based on the superposition principle and reproduction procedure. Therefore, the algorithmic logic remains the same for the combinatorial SSS algorithm; however, some components are modified to suit combinatorial problems. Performance of the combinatorial SSS algorithm is tested on the well-known combinatorial optimization problems such that the vehicle routing problem with simultaneous pickup and delivery, the vehicle routing problem with mixed pickup and delivery, the flow shop scheduling problem, and the job shop scheduling problem. This paper also compares the SSS algorithm against different solution approaches in the related literature on routing and scheduling problems. Experimental results indicate that the SSS algorithm has satisfactory performance and high capability in solving combinatorial optimization problems.

单搜寻者社会（SSS）算法是最近开发的用于解决复杂的连续优化问题的元启发式算法。本文的目的是使SSS算法适应组合优化问题。与原始SSS算法一样，组合SSS算法也将几种基于单解的搜索算法组合在一起，同时使它们通过基于叠加原理和再现过程的信息机制进行通信。因此，组合SSS算法的算法逻辑保持不变。但是，对某些组件进行了修改以适合组合问题。在众所周知的组合优化问题上测试了组合SSS算法的性能，例如在同时取货和交付的车辆路径问题，混合取货和配送的车辆路径问题，流水车间调度问题和作业车间调度问题。本文还将SSS算法与相关文献中有关路由和调度问题的不同解决方案进行了比较。实验结果表明，SSS算法在解决组合优化问题上具有令人满意的性能和较高的能力。