Crowdshipping: An open VRP variant with stochastic destinations

E-commerce continues to grow throughout the world due people’s preference stay at home rather than going a brick-and-mortar retail store. COVID-19 has exacerbated this trend. Concurrently, crowd-shipping been gaining in popularity both increase e-commerce and current pressures COVID-19. We consider setting where platform can fulfill heterogeneous delivery requests from central depot with fleet of professionally driven vehicles pool capacitated occasional drivers. divide into sectors represent different neighborhoods city. Occasional drivers have unknown destinations that be anywhere inside sectors. Route duration constraints are modeled motivate participation probability route-acceptance by keeping routes short. assume will choose better compensated is dependent on other being offered. propose two-stage stochastic model formulate problem. use branch-and-price algorithm capable solving 50-customer instances, develop heuristic solve larger 100-customer instances quickly. An upper bound for total number used reduce master problem complexity pricing problems. show far cost over 30%, while near 20%. route capacity restrict driver need simultaneously order reductions. This viable option last-mile deliveries.