基于改进遗传算法的供应链网络规划优化问题

Q3 Mathematics

International Journal for Simulation and Multidisciplinary Design Optimization Pub Date : 2023-01-01 DOI:10.1051/smdo/2023014

Liang Zhao, Jing Xie

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引用次数: 0

摘要

供应链网络的规划问题与物流成本和产品质量密切相关。本文针对供应链网络规划问题的优化，以农户与超市直接对接模式下的农产品供应链网络为例，建立了以成本最低为目标的农产品供应链网络规划模型。然后，设计了一种改进的遗传算法(GA)来求解模型。算例分析表明，与传统遗传算法相比，改进遗传算法的总成本为39,004.48美元，比传统遗传算法低6.5%;改进遗传算法的求解结果也优于其他启发式算法，如粒子群算法和蚁群算法。实验结果表明，改进遗传算法对供应链网络规划问题的优化是有效的，可以在实际中应用。

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Optimization of the supply chain network planning problem using an improved genetic algorithm

The planning problem of supply chain network is highly related to logistics cost and product quality. In this paper, for the optimization of supply chain network planning problem, an agricultural product supply chain network under the direct docking model between farmers and supermarkets was taken as an example to establish an agricultural product supply chain network planning model with the lowest cost as the objective. Then, an improved genetic algorithm (GA) was designed to solve the model. The analysis of the arithmetic example showed that compared with the traditional GA, the total cost obtained by the improved GA was lower, at 39,004.48 $, which was 6.5% less than that of the traditional GA; the solution result of the improved GA was also superior to that of other heuristic algorithms, such as particle swarm optimization and ant colony optimization. The experimental results demonstrate the optimization effectiveness of the improved GA for the supply chain network planning problem, and it can be applied in practice.

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来源期刊

International Journal for Simulation and Multidisciplinary Design Optimization Mathematics-Control and Optimization

CiteScore

2.00

自引率

0.00%

发文量

审稿时长

16 weeks

期刊介绍： The International Journal for Simulation and Multidisciplinary Design Optimization is a peer-reviewed journal covering all aspects related to the simulation and multidisciplinary design optimization. It is devoted to publish original work related to advanced design methodologies, theoretical approaches, contemporary computers and their applications to different fields such as engineering software/hardware developments, science, computing techniques, aerospace, automobile, aeronautic, business, management, manufacturing,... etc. Front-edge research topics related to topology optimization, composite material design, numerical simulation of manufacturing process, advanced optimization algorithms, industrial applications of optimization methods are highly suggested. The scope includes, but is not limited to original research contributions, reviews in the following topics: Parameter identification & Surface Response (all aspects of characterization and modeling of materials and structural behaviors, Artificial Neural Network, Parametric Programming, approximation methods,…etc.) Optimization Strategies (optimization methods that involve heuristic or Mathematics approaches, Control Theory, Linear & Nonlinear Programming, Stochastic Programming, Discrete & Dynamic Programming, Operational Research, Algorithms in Optimization based on nature behaviors,….etc.) Structural Optimization (sizing, shape and topology optimizations with or without external constraints for materials and structures) Dynamic and Vibration (cover modelling and simulation for dynamic and vibration analysis, shape and topology optimizations with or without external constraints for materials and structures) Industrial Applications (Applications Related to Optimization, Modelling for Engineering applications are very welcome. Authors should underline the technological, numerical or integration of the mentioned scopes.).