具有成本约束的设备投资木桶—贪婪优化算法研究

针对以经验为主的混合流水车间设备购置策略所导致的生产不平衡问题，提出了一种木桶—贪婪算法。该算法在固定设备成本的约束下，以产线生产节拍最快为目标，利用木桶效应的补短板思路识别出瓶颈工序，并在此基础上针对产线内多种类产品瓶颈工序不一致的特性引入贪婪思想。然后，基于实际产线案例对比不同算法的求解结果，木桶—贪婪算法相比穷竭搜索算法以及改进遗传算法在求解质量和效率方面具有一定优势。最后，以实际产线为背景，利用Plant Simulation仿真进行产线改造前后对比，验证了提出的算法在实际生产中的可行性和有效性。

Research on barrel-greedy optimization algorithm for equipment investment with cost constraints

Aiming at the problem of production imbalance caused by experience-based equipment purchase strategy in hybrid flow shop, this paper proposed a barrel-greedy algorithm. Under the constraint of fixed equipment cost, this algorithm took the fastest production cycle of the production line as the goal, and used the short board idea of barrel effect to identify the bottleneck process, and on this basis, it introduced the greedy idea for the inconsistent characteristics of the bottleneck processes of multiple products in the production line. Then, comparing the solution results of different algorithms based on the actual production line case, the barrel-greedy algorithm has certain advantages in solving quality and efficiency compared with exhaustive search algorithm and improved genetic algorithm. Finally, taking the actual production line as the background, this paper used Plant Simulation to compare the production line before and after transformation, and verifies the feasibility and effectiveness of the algorithm in practical production.