Hybrid differential evolution algorithm and genetic operator for multi-trip vehicle routing problem with backhauls and heterogeneous fleet in the beverage logistics industry

Abstract Logistics is increasingly challenging because of increased competition and the uncertainty introduced by globalization. The drinks distribution system considered here uses glass bottles for soft drinks to deliver to all customers who need soft drinks in glass bottles, before making any pickups of empty glass bottles from clients to return to the company. This study aims at both an integer linear programming formulation and a novel hybrid differential evolution algorithm involving a genetic operator with fuzzy logic controller, for solving the multi-trip vehicle routing problem with backhauls and a heterogeneous fleet. The objective function is to minimize total cost, which is related to distance travelled. For validation, we designed numerical experiments to compare the proposed approaches with LINGO computational software, using the conventional differential evolution algorithm and differential evolution with selected genetic operator and fuzzy logic controller in real settings. The experimental results demonstrate the practical viability of the proposed approaches.