Abstract
The biggest challenge that retailers face in satisfying consumer requirements is to ensure an integrated/seamless shopping experience consistent with the purchase, regardless of how the purchase is made. Giant companies have many depots, points of delivery, retail stores, etc. in different cities. This study focused on modeling vehicle routing in a retail distribution network. Goods may be sold in the distribution system addressed in the research model employing two methods: physical and online sales. This study examined the routing problem in the Omni-Channel (OC) retail system, focusing on a multi-objective approach to increase consumer physical convenience (ease of access) using several delivery techniques from six points of delivery. To this end, the optimization of a distribution network was examined through two objective functions. The first objective function minimized the cost of the distribution network, whereas the second maximized customer convenience in terms of the minimum shipment delivery time from the four positions (retail store, intermediate depot, points of delivery, and city distribution center by considering the demand for each product). Two meta-heuristic algorithms, MOGWO and NSGA-II, were used to solve the problem. The results demonstrate that the two-step approach generates smaller objective function values than the second objective function. In addition, the total costs of the two-stage approach were higher than those predicted by the proposed model. Consequently, it was concluded that, in the proposed mathematical model, owing to the integrated optimization of a distribution system and considering the possibility of direct shipment of products to customers, Pareto points are obtained with a lower cost and higher customer satisfaction.
•Examines routing in the OC retail system.•Focuses on a multi-objective approach to increase consumer physical convenience.•Using several delivery techniques from six delivery points.•Using two meta-heuristic MOGWO and the NSGA-II algorithms were used to solve the problem.