Sustainable Multi-objective land use optimization: Application of parallel simulated annealing (PSA) algorithm (Case study: Baboldasht district of Isfahan)

A heuristic method named as parallel simulated annealing is developed for multi-objective land use allocation based on the concept of sustainable development which is the predominant notion of land use planning. Numerous plans are generated and optimized by this algorithm according to land use allocation objectives: maximizing compatibility, compactness, green area, commercial area and floor area ratio. These objectives and constraints are formulated and combined through weighted sum method. This paper moves the previous studies forward in several aspects: ) application of non-linear objective functions which represent the complexity of real word better than linear functions, ) development of a PSA-based meta-heuristic for solving land use allocation problem, and ) adding density related objective functions which represent the concept of sustainable development more comprehensive. Application of PSA algorithm in land use allocation of Baboldasht district, demonstrates effectiveness and the potential of this algorithm in development of planning support system through representation of optimal solutions with different preferences. Also the comparison between the proposed algorithm and non-dominated sorting genetic algorithm-II (NSGA-II) represents that the PSA is better than NSGA-II in terms of quality and efficiency.

Keywords:

Parallel simulated annealing , land use allocation , NSGA-II , optimization