Cooperative Operation Optimization of Sorting and Refrigerated Trucks for Fresh Agricultural Products
The paper focuses on the cooperative operation optimization of sorting and refrigerated trucks in the"first-mile"cold chain transportation for fresh agricultural products.It employs methods such as space-time-state network modeling and lagrangian relaxation algorithm to address the challenges.The primary focus is on decomposing multidimensional complex combinatorial optimization problems,particularly emphasizing the construction of an optimization model for the cooperative operation optimization of moving sorting and refrigerated trucks based on space-time-state network.Additionally,it designs a solution method based on the lagrangian relaxation algorithm and greedy rules to achieve dimension reduction decomposition of large-scale high-dimensional networks,thereby enhancing algorithm efficiency.Comparative analyses with the CPLEX commercial solver through numerical experiments validate the algorithm's performance in solving large-scale problems.Sensitivity analysis is conducted to study the impact of unit travel costs on system operation states.By employing space-time-state network modeling,the study provides new insights into reducing the complexity of multi-stage cooperative operation optimization modeling and offers novel methods for efficiently solving large-scale multidimensional network optimization problems.
万方数据
维普
