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.