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首页> 外文期刊>Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies >Modified Cuckoo Optimization Algorithm (MCOA) to solve Precedence Constrained Sequencing Problem (PCSP)
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Modified Cuckoo Optimization Algorithm (MCOA) to solve Precedence Constrained Sequencing Problem (PCSP)

机译:修改的Cuckoo优化算法(MCOA)解决优先限制的测序问题(PCSP)

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摘要

In recent years, new meta-heuristic algorithms have been developed to solve optimization problems. Recently-introduced Cuckoo Optimization Algorithm (COA) has proven its excellent performance to solve different optimization problems. Precedence Constrained Sequencing Problem (PCSP) is related to locating the optimal sequence with the shortest traveling time among all feasible sequences. The problem is motivated by applications in networks, scheduling, project management, logistics, assembly flow and routing. Regarding numerous practical applications of PCSP, it can be asserted that PCSP is a useful tool for a variety of industrial planning and scheduling problems. However it can also be seen that the most approaches may not solve various types of PCSPs and in related papers considering definite conditions, a model is determined and solved. In this paper a new approach is presented for solving various types of PCSPs based on COA. Since COA at first was introduced to solve continuous optimization problems, in order to demonstrate the application of COA to find the optimal sequence of the PCSP, some proposed schemes have been applied in this paper with modifications in operators of the basic COA. In fact due to the discrete nature and characteristics of the PCSP, the basic COA should be modified to solve PSCPs. To evaluate the performance of the proposed algorithm, at first, an applied single machine scheduling problem from the literature that can be formulated as a PCSP and has optimal solution is described and solved. Then, several PCSP instances with different sizes from the literature that do not have optimal solutions are solved and results are compared to the algorithms of the literature. Computational results show that the proposed algorithm has better performance compared to presented well-known meta-heuristic algorithms presented to solve various types of PCSPs so far.
机译:近年来,已经开发出新的元启发式算法来解决优化问题。最近引入的咕咕优化算法(COA)已证明其优异的性能来解决不同的优化问题。优先限制约束序列问题(PCSP)与定位最佳序列与所有可行序列之间的最短行驶时间定位有关。问题是通过网络,调度,项目管理,物流,装配流程和路由的应用程序激励。关于PCSP的许多实际应用,可以断言PCSP是各种工业规划和调度问题的有用工具。然而,还可以看出,考虑确定的条件,最多的方法可能无法解决各种类型的PCSP和相关论文,确定并解决了模型。本文提出了一种新方法,用于基于COA解决各种类型的PCSP。由于首先引入COA来解决连续优化问题,为了证明COA的应用找到PCSP的最佳顺序,本文已应用了一些提出的方案,并在基本COA的运营商中进行了修改。事实上,由于PCSP的离散性质和特征,应修改基本COA以解决PSCP。为了评估所提出的算法的性能,首先,从文献中可以将其作为PCSP配制的应用单机调度问题并具有最佳解决方案。然后,解决了具有没有最佳解决方案的文献中具有不同大小的多种PCSP实例,并将结果与​​文献的算法进行了比较。计算结果表明,与呈现众所周知的元启发式算法相比,该算法具有更好的性能,以旨在解决各种类型的PCSP。

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