Using Ant Colony Optimization Metaheuristic in Forest Transportation Planning

Timber transportation is one of the most expensive activities in forest operations. Traditionally, the goal of forest transportation planning has been to find the combination of road development and harvest equipment placement that minimizes total harvesting and transportation costs. However, modern transportation problems are not driven only by economics of timber management, but also by multiple uses of roads and their social and ecological impacts. These social and environmental considerations and requirements introduce side constraints into the forest transportation planning, making the problems larger and more complex. We developed a new problem solving technique using the ant colony optimization (ACO) metaheuristic, which is able to solve large and complex transportation planning problems with side constraints. We considered the environmental impact of forest road networks represented by sediment yields as side constraints. Results on a hypothetical transportation problem show that this algorithm (ACO-FTPP) is promising for solving real forest transportation planning problems with side constraints. A description of the development of the algorithm and its search process is presented.