A novel hybrid genetic algorithm for the location routing problem with tight capacity constraints

摘要: Abstract Location routing problem (LRP) is a popular and challenging topic in the field of logistic systems. LRP needs to address depot location vehicle at same time. Till now, different variants have been formulated better meet realistic requirements. In this study, we focus on capacitated (CLRP) with tight capacity constraint both depots vehicles. To cope constraints, hybrid genetic algorithm (HGA) developed search not only feasible solution space but also infeasible space. The proposed HGA combines wide exploration GA, fast exploitation neighbourhood local search. evolve GA for CLRP, solutions are represented by sets sequences, accordingly, multi-sequence-based crossover designed offspring generation. Moreover, population management scheme facilitate GA’s evolution. Experiments conducted two benchmark results show that quite competitive existing well-known CLRP algorithms classical instances. Furthermore, able obtain number new best real-life-like instances tighter constraints.