HYBRID GREY WOLF OPTIMISATION ALGORITHM FOR JOB SHOP SCHEDULING PROBLEM

This research investigates the application of the Hybrid Grey Wolf Optimization Algorithm (HGWOA) for solving the Job Shop Scheduling Problem (JSSP), a combinatorial optimization challenge prevalent in production management. The primary objective is to minimize makespan, the total time required to complete all jobs on a set of machines while adhering to precedence constraints. Traditional optimization techniques often struggle with complex JSSP instances due to its NP-hard nature. We propose a novel approach integrating the Grey Wolf Optimization Algorithm (GWOA) with other metaheuristic techniques to enhance its performance in solving JSSP. Experimental results demonstrate the effectiveness of HGWOA, highlighting its potential for real-world applications in production scheduling and management.