考虑随机需求和时间约束LIRP联合协同优化

针对多节点多层次多功能的供应链管理中整体效益亟待提高的问题，结合某连锁超市的单一供应商、多分销中心、多零售店所构成二级分销网络，建立以系统总成本和供货时间为目标的多目标选址-库存-路径问题（location-inventory-routing?problem，LIRP）集成规划模型. 利用线性加权法将其转化为单目标规划模型，提出遗传算法和节约里程法相结合的两阶段启发式算法并求解模型，第1阶段用遗传算法求解选址-库存问题，第2阶段用节约里程算法求解车辆路径规划问题. 并结合某连锁超市实例，对不同总成本权重下的不同决策方案的分销网络进行LIRP集成优化，优化后的系统方案比原文献的总里程减少了3 606.9 km，系统总成本减小了6 526.2 元，缺货成本降低了124.6 元，只有19.7元，验证了模型和算法的有效性. 

LIRP Joint Collaborative Optimization under Stochastic Demand and Time Constraints

Aiming at improving the overall efficiency of the multi-node, multi-level, and multi-functional supply chain management, a secondary distribution network composed of a single supplier, multiple distribution centers, and multiple retail stores for a chain supermarket wasexplored to establish the multi-objective location-inventory-routing problem (LIRP) integrated planning model with the objectives of the total system cost and supply time. The linear weighting method was used to transform the model into the single-objective programming one. A two-stage heuristic algorithm combining genetic algorithm and mileage saving method was proposed to solve the model. In the first phase, the location-inventory problem was solved by the genetic algorithm, and in the second phase, vehicle routing problem was solved by the mileage saving method. A chain supermarket example was used for the LIRP integration optimization of the distribution network with different decision schemes and total cost weights. Compared the results from a reference, the optimized system scheme reduced the total mileage by 3 606.9 km, the total system cost by 6 526.2 yuan, and the cost of back orders by 124.6 yuan, being 19.7 yuan, which verifies the model and algorithm.