Generally, medium and large electromechanical maintenance vendors have more than one distribution station. These require routine inspections and maintenance to continue the normal operations of distribution station equipment. Therefore, in this study, we divided routine maintenance time into annual, seasonal, and monthly cycles to develop the optimal inspection route and reduce maintenance costs. We selected 31 universities in Taiwan as the distribution station locations for testing. We used Google My Maps to establish each university’s geographical location and to query the traffic time and distance between each university. Finally, maintenance and traffic times were incorporated into the working time and inputted into a particle swarm optimization. The working time and distance traveled were calculated to optimize the inspection route. The test results indicate that the particle swarm optimization performed better than the genetic algorithm for inspection route optimization. The computer execution time of applying the particle swarm optimization was 0.85 s when performing multi-point inspection optimal route planning for the 31 distribution stations. Therefore, particle swarm optimization could significantly reduce route planning time and inspection costs while achieving smart route optimization goals.