Transactions of Nanjing University of Aeronautics & Astronautics
An Improved Genetic Algorithm for Solving the Mixed-Flow Job-Shop Scheduling Problem with Combined Processing Constraints
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Abstract:
The flexible job-shop scheduling problem（FJSP） with combined processing constraints is a common scheduling problem in mixed-flow production lines. However， traditional methods for classic FJSP cannot be directly applied. Targeting this problem， the process state model of a mixed-flow production line is analyzed. On this basis， a mathematical model of a mixed-flow job-shop scheduling problem with combined processing constraints is established based on the traditional FJSP. Then， an improved genetic algorithm with multi-segment encoding， crossover， and mutation is proposed for the mixed-flow production line problem. Finally， the proposed algorithm is applied to the production workshop of missile structural components at an aerospace institute to verify its feasibility and effectiveness.
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Clc Number:
TH165
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