Mathematical model and genetic algorithm for distribution logistics problem with maximum route length

Abstract

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 pick-up (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.