Multi-objective Optimization for Location-Routing-Inventory Problem in Cold Chain Logistics Network with Soft Time Window Constraint

With the improvement of enterprise services, location-routing-inventory problem with time window constraint (LRIPTW) has become an essential problem in cold chain logistics network (CCLN). This paper aims to optimize the location cost, inventory cost, transportation cost, and penalty cost in CCLN simultaneously. Firstly, an optimization model was established for the LRIP with soft time window constraint (STW). Then, the multi-objective ant colony optimization (MACO) was improved to solve the model. Simulation results show that the improved MACO can solve the LRIPSTW effectively and efficiently. The research findings provide a reference for enterprises to reduce total cost and improve service quality.