Combining hybrid genetic search with ruin-and-recreate for solving the capacitated vehicle routing problem

Abstract The Capacitated Vehicle Routing Problem (CVRP) has been subject to intense research efforts for more than sixty years. Yet, significant algorithmic improvements are still being made. most competitive heuristic solution algorithms of today utilize, and often combine, strategies elements from evolutionary algorithms, local search, ruin-and-recreate based large neighborhood search. In this paper we propose a new hybrid metaheuristic the CVRP, where education phase genetic search (HGS) algorithm proposed by (Vidal Hybrid Genetic Search CVRP: Open-Source Implementation SWAP* Neighborhood 2020) is extended applying (LNS). By performing series computational experiments, attempt answer following questions: 1) Is it possible gain performance adding LNS as component in HGS? 2) How does addition change relative importance neighborhoods 3) What effect devoting creation an elite initial population Through set experiments these questions, while at same time obtaining good configuration global parameter settings heuristic. Testing on benchmark instances literature with limited computing time, outperforms existing both terms final gap primal integral.