基于量子粒子群求解多制程订单选择问题

针对订单选择问题，考虑订单具有不同制程的特征，建立了以总收益为目标的混合整数非线性规划模型。以量子粒子群优化算法为框架进行求解，采用基于排序的粒子编码方案表达0-1变量和整数变量，提出四种种群初始化策略以便提高求解质量，并在迭代过程中对不可行解进行修复。通过对比验证，结果表明模型和算法可行、有效。

Quantum PSO algorithm for order selection problem with multiple process routes

Considering the characteristic of multiple process routes, this paper focuses on the order selection problem. A mixed integer non-linear programming model is built with objective of maximizing the total profits. A quantum-behaved PSO-based algorithm is employed as solution mainframe in which a sequence-based particle coding solution is designed to represent decision variables and integer variables and four population initiation strategies are proposed to improve the solution quality. A repair mechanism for infeasible solutions is adopted in iteration. By computational comparison tests, it can be proven that the model and algorithm are feasible and effective.