Parallel Scheduling of Machines and Tools without Tool Delay Using Symbiotic Organisms Search Algorithm

This work presents a novel approach for parallel scheduling of machines and tools without tool delay in the automobile manufacturing industry using a symbiotic organisms search algorithm (SOSA). This paper proposes nonlinear mixed integer programming (MIP) formulation to model simultaneous scheduling problems. The mutualistic relationship between different species in nature inspires the proposed algorithm. It aims to optimize the scheduling process by minimizing the makespan (MSN) while ensuring no tool delay during the production process. The algorithm is implemented in a parallel computing environment to speed up the search process and handle scheduling problems. Experimental results show that the proposed approach outperforms existing methods in terms of solution quality and computational efficiency. This work offers a promising solution for real-world manufacturing scheduling problems with multiple machines and tools, often characterized by complex constraints and uncertainties.