Value chain collaboration management is an effective means for enterprises to reduce costs and increase efficiency to enhance competitiveness. Vertical and horizontal collaboration have received much attention, but the current collaboration model combining the two is weak in terms of task assignment and node collaboration constraints in the whole production-distribution process. Therefore, in the enterprise dynamic alliance, this paper models the MVC (multi-value-chain) collaboration process for the optimization needs of the MVC collaboration network in production-distribution and other aspects. Then a MVC collaboration network optimization model is constructed with the lowest total production-distribution cost as the optimization objective and with the delivery cycle and task quantity as the constraints. For the high-dimensional characteristics of the decision space in the multi-task, multi-production end, multi-distribution end, and multi-level inventory production-distribution scenario, a genetic algorithm is used to solve the MVC collaboration network optimization model and solve the problem of difficult collaboration of MVC collaboration network nodes by adjusting the constraints among genes. In view of the multi-level characteristics of the production-distribution scenario, two chromosome coding methods are proposed: staged coding and integrated coding. Moreover, an algorithm ERGA (enhanced roulette genetic algorithm) is proposed with enhanced elite retention based on a SGA (simple genetic algorithm). The comparative experiment results of SGA, SEGA (strengthen elitist genetic algorithm), ERGA, and the analysis of the population evolution process show that ERGA is superior to SGA and SEGA in terms of time cost and optimization results through the reasonable combination of coding methods and selection operators. Furthermore, ERGA has higher generality and can be adapted to solve MVC collaboration network optimization models in different production-distribution environments.

中文翻译：

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多价值链中生产分配的优化方法。

价值链协同管理是企业降本增效、增强竞争力的有效手段。纵向和横向协同备受关注，但目前将两者结合的协同模式在生产配送全流程的任务分配和节点协同约束方面薄弱。因此，本文在企业动态联盟中，针对MVC协作网络在产销等方面的优化需求，对MVC（多价值链）协作过程进行建模。然后以总产销成本最低为优化目标，以交付周期和任务数量为约束，构建了MVC协作网络优化模型。针对多任务、多生产端、多配送端、多级库存生产配送场景下决策空间的高维特性，采用遗传算法求解MVC协同网络优化模型，通过调整基因间的约束，解决MVC协作网络节点协作困难的问题。针对产销场景的多层次特点，提出了两种染色体编码方法：分阶段编码和综合编码。此外，还提出了一种基于SGA（简单遗传算法）的增强型精英保留算法ERGA（增强型轮盘遗传算法）。SGA、SEGA（强化精英遗传算法）、ERGA、对种群演化过程的分析表明，通过编码方式和选择算子的合理组合，ERGA在时间成本和优化结果上均优于SGA和SEGA。此外，ERGA具有更高的通用性，可以适用于解决不同产销环境下的MVC协作网络优化模型。