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The new TOPCO hybrid algorithm to solve multi-objective optimisation problems: the integrated stochastic problem of production-distribution planning in the supply chain

机译:新的Topco混合算法解决了多目标优化问题:供应链中生产分布规划的集成随机问题

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This paper presents a new hybrid algorithm to solve multi-objective optimisation problems called TOPCO which has been implemented on the integrated stochastic problem of production-distribution planning in the supply chain. The proposed TOPCO hybrid algorithm is a combination of the TOPSIS algorithm and the cuckoo optimisation algorithm and is therefore named TOPCO. The cuckoo optimisation algorithm is unable to solve multi-objective problems that can be easily used for multi-objective problems using the proposed hybrid approach. The multi-objective problem under study includes an integrated model of production and distribution planning with many stochastic parameters. The speed and accuracy of the results obtained from the implementation of the proposed TOPCO algorithm on the supply chain problem show the efficiency of the algorithm in solving multi-objective problems and this algorithm can well identify the Pareto frontier of the problem. Also, due to the use of the cuckoo optimisation algorithm, the proposed TOPCO algorithm can be used in large-scale problems.
机译:本文介绍了一种新的混合算法,解决了在供应链中生产分布规划的集成随机问题上实现了多目标优化问题。所提出的Topco混合算法是TopSIS算法和Cuckoo优化算法的组合,因此被命名为Topco。 Cuckoo优化算法无法解决使用所提出的混合方法可以轻松地用于多目标问题的多目标问题。研究下的多目标问题包括具有许多随机参数的生产和分配规划的集成模型。从实施中所提出的Topco算法的实施方式获得的结果的速度和准确性显示了算法在解决多目标问题时算法的效率,并且该算法可以很好地识别问题的帕累托前沿。此外,由于使用杜鹃优化算法,所提出的Topco算法可以用于大规模问题。

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