Land use optimization through harmonic search meta-heuristic algorithm (Case study: Baboldasht district of Isfahan)

Urban planning seeks to allocate the valuable and limited land resources among different land types. During this process various conflicting objectives are emerged and prepared, and land use planners should proffer land use layouts satisfying these kinds of objectives. Due to these facts, land use allocation is a multi-objective optimization problem that deals with a large set of data and variables and optimization methods have been developed to facilitate solving this kind of problem. As land use optimization is a complex NP-hard problem, current exact methods are not able to solve such problem and land use optimization relies on application of meta-heuristic algorithms. In this paper, a meta-heuristic algorithm is developed and applied based on harmonic search algorithm for solving land use optimization problem. In this paper, seven land types (residential, commercial, cultural, educational, medical, sport and green space) are allocated to 200 allocation cells with size 1000 m2 subject to compactness, compatibility and suitability maximization. The outputs of the harmonic search algorithm were compared to a common population-based algorithm, genetic algorithm. The results demonstrated that for the defined problem the harmonic search algorithm was more acceptable than genetic algorithm in terms of solution quality and algorithm efficiency. It was 98.9 percent faster than genetic algorithm. The results also showed that the land use layouts achieved by both algorithms had been better than the current state of land use distribution. Thus, the cross-cutting method represented in this paper can be used as a useful tool in the hands of urban planners and decision makers, and supports the land use planning process.