Mathematical Model And Genetic Algorithm For Distribution Logistics Problem With Maximum Route Length

摘要

Logistics is no longer seen as tactical and cost-driven - it is strategic. Considering the driver-on-time rules and with the perishable nature of the products, the travel length/time is one of the critical constraints in distribution logistics. We consider a typical logistics problem with maximum route length constraint. The variant is termed as simultaneous delivery and pick-up with maximum route length (SDPM). We developed a unified mixed-integer-linear programming (MILP) model and genetic algorithm to solve SDPM and the standard variant, vehicle routing problem with simultaneous delivery and pickup (VRPSDP). Benchmark datasets for VRPSDP and randomly generated datasets for SDPM are solved using MILP model and genetic algorithm and the results are compared with best-known solution. The results of genetic algorithm are encouraging.