A hyper heuristic for the green vehicle routing problem with simultaneous pickup and delivery

This paper studies the green vehicle routing problem with simultaneous pickup and delivery (G-VRPSPD). It aims to minimize fuel consumption costs while satisfying customer pickup and delivery demands simultaneously. The fuel consumption is directly proportional to green house gas emissions. We mathematically formulate the problem, and develop a hyper-heuristic (HH-ILS) algorithm based on iterative local search and variable neigh-borhood descent heuristics to effectively solve the problem. Extensive computational experiments are conducted to analyze the impact of the G-VRPSPD and the HH-ILS. We investigate the effect of green objective function on total fuel consumption cost by comparing the G-VRPSPD with the VRPSPD. We perform comparative analysis to investigate the performance of HH-ILS. We also conduct sensitivity analysis to investigate the performance of neighborhood structures, hyper heuristic and local search. The results show that the green objective function has a significant effect on total fuel consumption cost. The HH-ILS algorithm yields competitive results when compared with the mathematical formulation and the state-of-the-art heuristics in the literature.