Abstract: According to the characteristics of collaboration under supply chain environment, the optimal allocation of production capacity oriented to downstream enterprises demand was studied. Aiming at the enterprise profit maximization, the equipment utilization ratio and the demand saturation of downstream enterprises, a deliverability optimizing allocation model was established, and a multi-objective particle swarm optimization algorithm was designed based on elite set. Combined with the constraints feature of model, the fitness function based on penalty function thought was designed by using constraint-satisfaction technology, and repair rules for infeasible solution were proposed. Aiming at the features of multi-objective optimization, the elite set was established to save non-inferior solution, and the elite set was updated with Pareto optimal theory. Based on elite set pruning strategy of k-means clustering, the scale of elite set and the distribution of particle were ensured. Experiment results showed the effectiveness and feasibility of proposed model and algorithm.

Key words: supply chains, optimal allocation of production capacity, particle swarm optimization, multi-objective optimization

摘要： 针对供应链环境的协作特征，研究以下游企业需求为导向的产能优化配置，建立了以最大化企业盈利、设备利用率以及下游企业需求饱和度为目标的问题模型，并设计了基于精英集的多目标粒子群算法。算法结合模型的约束特征，采用约束满足技术生成初始解，基于惩罚函数的思想设计适应度函数，并对不可行解提出了修复规则；针对多目标优化特征，在求解过程中通过建立精英集来保存非劣解，并基于Pareto最优的概念更新精英集，利用基于k-means聚类的精英集裁剪策略，来保证精英集规模和粒子的分布性。实验结果表明了模型和算法的可行性和有效性。

关键词: 供应链, 产能优化配置, 粒子群优化算法, 多目标优化