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引用次数: 13
摘要
在使用作业车间调度生产系统(Job Shop scheduling production system, JSP)时,如何在多台机器上高效地调度作业是一个重要的考虑因素。JSP是一个np困难问题,因此专注于生成精确解的方法可能不足以找到JSP的最佳解决方案。因此,在这种情况下,启发式方法可以在合理的时间内找到一个好的解决方案。本文在研究传统蚁群算法的基础上,提出了一种适用于JSP的负载均衡蚁群算法。我们还给出了观测结果,并与常规蚁群算法进行了讨论。实验结果表明,与传统蚁群算法相比,该算法具有更好的优化效果。
A modified Ant Colony optimization algorithm with load balancing for job shop scheduling
The problem of efficiently scheduling jobs on several machines is an important consideration when using Job Shop scheduling production system (JSP). JSP is known to be a NP-hard problem and hence methods that focus on producing an exact solution can prove insufficient in finding an optimal resolution to JSP. Hence, in such cases, heuristic methods can be employed to find a good solution within reasonable time. In this paper, we study the conventional ACO algorithm and propose a Load Balancing ACO algorithm for JSP. We also present the observed results, and discuss them with reference to the conventional ACO. It is observed that the proposed algorithm gives better results when compared to conventional ACO.