Abstract:

In the “Port before Factory” mode, the port provides high-quality value-added services for steel mill production operations, forming a “chain” and “chain” alliance with the port service supply chain and the steel mill production supply chain. In addition, a fair and reasonable benefit distribution plan is a key factor affecting the stability and performance of the alliance. Therefore, in order to promote the effective operation of the “Port before Factory” supply chain alliance, this paper, taking into account the characteristics of the “chain” and “chain” alliances, considering the factors of service contribution and service duration, and aiming at maximizing the overall benefit of the alliance, constructs a benefit distribution model. However, because the model is non-linear, non-differentiable, and requires high accuracy of the results, a bacterial foraging optimization algorithm with a wide search range and a large evolutionary space is selected to solve the problem. The new algorithm combining foraging dynamics and the foraging optimization algorithm designed in this paper overcomes the defect of the poor stability caused by the uncertain flip direction of a single foraging optimization algorithm, which improves the accuracy and stability of the algorithm. The simulation verification using Python shows that the result of benefit distribution conforms to the principles of the overall rationality and individual rationality in the cooperative game theory, which proves that the benefit distribution model is fair and effective, and provides scientific basis and theoretical methods for the “integration of advanced manufacturing and modern service industries.”

Key words:

“the integration of advanced manufacturing and modern service industries”；profit distribution；contribution difference；foraging dynamics, improved bacterial foraging optimization algorithm（IBFOA）

摘要：

“前港后厂”模式下，港口为钢厂生产提供高质量的增值服务，形成了以港口服务供应链与钢厂制造供应链相辅相成的“链”与“链”联盟。而共生共赢的利益分配方案是影响联盟稳定与联盟绩效的关键因素。因此，为促进“前港后厂”供应链联盟有效运行，针对港口服务与钢铁制造“链-链”联盟的特点，考虑服务贡献度与服务时长差异，以联盟整体利益最大化为目标，构建了其利益分配模型。由于模型非线性、不可微，对结果精确性要求高，故选择搜索幅度广、进化空间大的细菌觅食优化算法求解。本文设计的觅食动力学与觅食优化算法相结合的新算法，克服了单一觅食优化算法翻转方向不确定导致其稳定性差的缺陷，提高了算法精确度及稳定性。使用Python语言仿真验证表明利益分配结果符合合作博弈理论中整体理性与个体理性原则，证明该利益分配模型公平高效，为制造业与服务业的“两业融合”提供了科学依据与理论方法。

关键词:

“两业融合”, 利益分配, 差异贡献度, 觅食动力学, 改进细菌觅食优化算法