Abstract

This paper focuses on the No-Wait Flow Shop Scheduling Problem and conducts research based on an improved Simulated Annealing Algorithm. The No-Wait Flow Shop Scheduling Problem is of great significance in practical production, but its solution complexity is high, requiring the search for appropriate optimization methods. In this study, a solution based on an improved Simulated Annealing Algorithm is proposed. Simulated Annealing Algorithm, as a global optimization method, introduces random perturbations to the current solution and accepts or rejects the new solution based on Metropolis criterion to escape local minima and search for better solutions. In this paper, the termination condition of the improved Simulated Annealing Algorithm is enhanced. Specifically, if no better solution is obtained after a certain number of consecutive temperature calculations or when the maximum number of outer loop iterations is reached, the algorithm terminates and outputs the result. This improvement aims to increase efficiency and reduce unnecessary computations.By comparing the results with other heuristic algorithms, it is found that the solution based on the improved Simulated Annealing Algorithm can effectively provide better scheduling solutions for the No-Wait Flow Shop Scheduling Problem, thereby improving production efficiency, reducing costs, and optimizing resource utilization.

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