NETWORK DESIGN FOR THE TEMPORAL AND SPATIAL COLLABORATION WITH SERVICE CLASS IN DELIVERY SERVICES
DOI:
https://doi.org/10.23055/ijietap.2023.30.1.8761Abstract
The COVID-19 pandemic has significantly impacted e-commerce and the delivery service sector. As lockdowns and social distancing measures were put in place to slow the spread of the virus, many brick-and-mortar stores were forced to close, leading to an increase in online shopping. This situation led to a surge in demand for delivery services as more people turned to the internet to purchase goods. However, this increase in demand also created several challenges for delivery companies. They experienced delays in delivering packages due to increased volume, limited staff, and disruptions to supply chains. It led to more competition and increased pressure on delivery companies to improve their services and delivery times. To overcome such competition, collaboration among small and medium-sized delivery companies can be a good way to compete with larger delivery companies. By working together, small and medium-sized companies can combine their resources and expertise to offer more extensive coverage and competitive prices than they could individually. This can help them to gain market share and expand their customer base. This study proposes a network design model for collaboration with service class in delivery services considering multi-time horizon. The problem to be considered is deciding which company is dedicated to delivering certain types of items, such as regular or refrigerated items, in designated regions in each time horizon. During the agreed-upon timeframe, the companies operate, using each other's infrastructure (such as vehicles and facilities) and sharing delivery centers for the coalition's benefit to improve efficiency and reduce costs. We also propose a multi-objective, nonlinear programming model that maximizes the incremental profit of participating companies and a linearization methodology to solve it. The max-sum criterion and Shapley value allocation methods are applied to find the best solution and ensure a fair distribution of profits among the collaborating group. The efficiency of the suggested model is shown through a numerical illustration.
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