Solving real-life combinatorial optimization problems using simulated annealing

Two real-life optimization problems, having combinatorial properties and with the same geometric structure, will be presented. These problems are the location of afforestation areas and nesting problems. Heuristic methods based on the principles of simulated annealing have been developed to solve the above mentioned problems. Computational experiences will be reported. Emphasis will be placed on the factors that determine a suitable implementation of simulated annealing based algorithms. A similar approach could be followed to solve other types of geometrical problems such as layout and location problems, clustering problems, and image processing.