In some areas of land planning, such as forest management, construction and development of cities, and choosing the right place to establish factories and industrial units, allocating land individually and in a scattered manner can cause problems. The approach can lead to inefficiencies and challenges in coordinating land use effectively. These problems increase the importance of the current research because the research aimed to provide a method to solve the problems. In this research, Meta Mola software has been introduced, which used metaheuristic algorithms to optimize land allocation in Gorgan Township in multi-objective problems. The main goal of this study was to provide an efficient method for contiguity and compactness land allocation using particle swarm (PSO) and firefly (FA) algorithms. By integrating metaheuristic algorithms and compactness and contiguity optimization capabilities, the software effectively modified the scattered patterns of the land and provided a more optimal allocation. One of the outstanding features of Meta Mola is the ability to use the Emgu graphical interface to identify key points and create reallocations that allow connection to GIS software. The results showed that this software, especially with an emphasis on contiguity and compactness, acts as a useful tool for land use planning with optimal performance in complex land allocation issues. The results can significantly help to reduce negative environmental effects and improve productivity in land planning. It also provides the basis for the development of sustainable development patterns.