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Parallel Ant Colony Optimization for Flow Shop Scheduling Subject to Limited Machine Availability

机译:受限机器可用性的流水车间调度并行蚁群优化

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In this paper, parallel ant colony algorithm (PAC) and parallel ant colony with local search algorithm (PACwLS) are presented and applied to Permutation Flowshop Scheduling Problem subject to limited machine availability. The objective is to minimize total flowtime criterion. This problem is proved to be NP-complete in a strong sense for more than one machine even when machines are always available. PAC and PACwLS are based on the classical ant colony algorithm, but are implemented and adapted on parallel computer systems with Message Passing Interface involving the communications and collaborations of multiple computing nodes. Computational experiments show that by comparing with monte carlo algorithm, both PAC and PACwLS ourperform monte carlo algorithm, and PACwLS consistently outperforms PAC and converges faster than both PAC and monte carlo algorithm.
机译:本文提出了并行蚁群算法(PAC)和带有局部搜索算法的并行蚁群算法(PACwLS),并将其应用于受限机器可用性的置换流水车间调度问题。目的是最小化总的流动时间标准。事实证明,即使一台机器始终可用,对于多台机器来说,这个问题在很大的意义上也是NP完全的。 PAC和PACwLS基于经典的蚁群算法,但在具有消息传递接口的并行计算机系统上实现并进行了修改,该消息传递接口涉及多个计算节点的通信和协作。计算实验表明,通过与蒙特卡洛算法进行比较,PAC和PACwLS均优于蒙特卡洛算法,而PACwLS始终优于PAC,并且收敛速度快于PAC和蒙特卡洛算法。

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