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With the improvement of quality of life and pursuit of a healthy diet, consumers’ demand for fresh agricultural products (FAPs) has grown steadily over the past decade. Examples of FAPs include fruits, vegetables, aquatic products, livestock, and other primary products. According to the Agrifood Industry 2023 Outlook (Allianz Trade, 2023), the global FAPs market recorded US$8.67 trillion in 2022 and is expected to reach US$12 trillion by 2027. The market has huge potential with the increase in purchasing channels, such as agricultural e-commerce, community group buying, and live broadcast selling (Zhao et al., 2021).
However, the perishable characteristics of FAPs may pose a challenge for distribution planning because the distribution paths must be planned with explicit consideration of freshness and quality requirements. Indeed, Han et al. (2021) pointed out that the main challenges facing agricultural logistics in China are high spoilage and deterioration rate, low distribution efficiency, and high logistics cost in the distribution process. The rapid reduction in FAPs quality during transportation requires they be delivered within consumer-specified times or time windows. Early or delayed delivery will result in lower consumer satisfaction with logistics service quality (Sun et al., 2022).
In addition to the agricultural products’ quality, increasing environmental concerns regarding distribution vehicles’ high fuel consumption and carbon emissions, particularly in cold chain distribution, have become an important factor for consideration in logistics and distribution planning. The optimization of FAPs logistics distribution considering various economic and environmental aspects has been extensively examined in the literature (Bortolini et al., 2016; Chen et al., 2020; Devapriya et al., 2017; Kwon et al., 2013; Li et al., 2020; Rong et al., 2011; Sun et al., 2022; Wang et al., 2020).
The key to improving FAPs logistics distribution systems lies in effective distribution path planning. The distribution path planning problem can also be viewed as the vehicle routing problem (VRP) (Dantzig & Ramser, 1959). In the context of FAPs distribution path optimization, the vehicle routing problem with time windows (VRPTW) is typically formulated to ensure timely delivery by distribution vehicles while achieving the shortest transportation distance (time) and, thus, the lowest transportation cost (e.g., Amorim et al., 2014; Chen et al., 2009; Hsu et al., 2007; Naso et al., 2007; Ombuki et al., 2006; Osvald & Stirn, 2008; Shukla & Jharkharia, 2013; Xia & Fu, 2019).
Xia and Fu (2019) pointed out that although serving consumers’ demand for FAPs with hard time-window requirements (i.e., when the delivery is made within the specified time window) is conducive to achieving high consumer satisfaction with logistics services, this may cause low vehicle utilization and restrict the choice of distribution paths. In turn, it will result in an increased number of vehicles and higher logistics distribution costs. For this reason, soft time windows (i.e., when delivery can be made outside the specified time window) would be more advantageous in terms of gaining flexibility in distribution routing.