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In this paper we intend to formulate a new metahueristic algorithm, called Open Source Development Model Algorithm (ODMA), for solving optimization problem. This algorithm inspired by open source development model and communities, In such way that each potential solution considered to be a software and by evolution the softwares, we search for better solutions to the function that should be optimized. The algorithm has two phases, initial phase and evolution phase. The evolution phase consist of moving to leading software, evolution of leading softwares is based on their history and forking from the leading softwares. We validate the proposed algorithm against benchmark function and then compare its performance with both of GA and PSO algorithms And according to results, we can see that the ODMA is much more efficient in finding the global optima and better accuracy than GA and PSO.
Note: As originally published there is an error in the article title: 'Metaheuristic' should be read instead of 'Metahueristic.' The metadata has been updated but the PDF file remains unchanged.