In forest region, walking environment is hybrid space mixed road networks and open space. People usually have diverse wayfinding objectives. In order to compute optimal walking path and provide wayfinding decision support, an optimal walking path analysis method for forest region (OWPAM-FR) was proposed. Firstly, the concept of walkability was introduced to build comprehensive walkability raster (CWR). Walking experiment in forest region was divided into unwalkable area, walkable area and easy-to-walk area. The special optimal walking path analysis problem can be transformed into a general multi-objectives least-cost path analysis problem in walkable area and easy-to-walk area. Secondly, walking costs were divided into terrain costs, including horizontal distance, spatial distance, slope, time and energy, and feature costs, including land cover and cognitive load. Single walking costs were computed and weighted, which were combined with comprehensive walking costs. The multi-objectives problem can be simplified as the single objective problem. Thirdly, adjacency list was extended and queen’s pattern was used to establish adjacency relationships of raster cells based on CWR. Then the comprehensive walking costs were computed and the raster network model was successfully established. Dijkstra algorithm was used to compute the optimal walking path. The results showed that OWPAM-FR can effectively model walking environment of forest region mixed open space and road networks. At the same time, the proposed method was able to reduce path cost of multiple wayfinding objectives and emphasis on different main objectives. In addition, OWPAM-FR composed of modeled steps had a certain applicability, which could be extended to several types of optimal walking path analysis applications, such as forest tourism, disaster relief and field investigation.