TY - JOUR
T1 - Multiroute fresh produce green routing models with driver fatigue using Type-2 fuzzy logic-based DFWA
AU - Thakur, Kishore
AU - Maji, Somnath
AU - Maity, Samir
AU - Pal, Tandra
AU - Maiti, Manoranjan
PY - 2023/11/1
Y1 - 2023/11/1
N2 - In developing countries, 40 percent of fresh fruits and vegetables are generally transported through nonrefrigerated vehicles and perishes before use, and wholesalers lose potential profits due to item rot. Here, a wholesaler's conveyance with fresh goods starts from a depot and returns to it after dropping the amounts at nodes (retailers) as per previously placed orders. As a perishable item's freshness (color and texture) changes with time, the item's selling price depends on its freshness at the time of delivery to retailers. There are multiple route connections among retailers and depots. Due to fatigue, the driver takes 15 minutes to rest after every two hours during the journey; otherwise, they are at risk of becoming overtired. Under these circumstances, multiroute fresh produce green routing models (MrFPGRMs) are formulated considering the product's freshness, optimum routing plan, appropriate routes, sales revenue, vehicle's running cost and speed, costs and times due to transportation and unloading, fixed charges, greenness (fuel cost), driver's salary and fatigue. The objective is to find the optimum routing plan, best-suited routes between the nodes, and vehicle velocity for the wholesaler's maximum profit, minimum fuel cost, or both. Virgin discrete fireworks algorithms are developed for the solution based on Type-1 and Type-2 fuzzy logic (T1FLDFWA and T2FLDFWA). Numerical experiments are performed through the T2FLDFWA for two time-dependent freshness functions, one of which is new. The results against driver rest, no rest, continuous journey risk, and a trade-off between profit and greenness are presented. Pareto fronts for multiobjectives are depicted. Some managerial decisions are observed.
AB - In developing countries, 40 percent of fresh fruits and vegetables are generally transported through nonrefrigerated vehicles and perishes before use, and wholesalers lose potential profits due to item rot. Here, a wholesaler's conveyance with fresh goods starts from a depot and returns to it after dropping the amounts at nodes (retailers) as per previously placed orders. As a perishable item's freshness (color and texture) changes with time, the item's selling price depends on its freshness at the time of delivery to retailers. There are multiple route connections among retailers and depots. Due to fatigue, the driver takes 15 minutes to rest after every two hours during the journey; otherwise, they are at risk of becoming overtired. Under these circumstances, multiroute fresh produce green routing models (MrFPGRMs) are formulated considering the product's freshness, optimum routing plan, appropriate routes, sales revenue, vehicle's running cost and speed, costs and times due to transportation and unloading, fixed charges, greenness (fuel cost), driver's salary and fatigue. The objective is to find the optimum routing plan, best-suited routes between the nodes, and vehicle velocity for the wholesaler's maximum profit, minimum fuel cost, or both. Virgin discrete fireworks algorithms are developed for the solution based on Type-1 and Type-2 fuzzy logic (T1FLDFWA and T2FLDFWA). Numerical experiments are performed through the T2FLDFWA for two time-dependent freshness functions, one of which is new. The results against driver rest, no rest, continuous journey risk, and a trade-off between profit and greenness are presented. Pareto fronts for multiobjectives are depicted. Some managerial decisions are observed.
KW - Driver's rest
KW - Fresh goods delivery system
KW - Meta-heuristics
KW - Routing
KW - Type-2 fuzzy logic
UR - http://www.scopus.com/inward/record.url?scp=85159762889&partnerID=8YFLogxK
U2 - 10.1016/j.eswa.2023.120300
DO - 10.1016/j.eswa.2023.120300
M3 - Journal article
SN - 0957-4174
VL - 229
JO - Expert Systems with Applications
JF - Expert Systems with Applications
IS - Part A
M1 - 120300
ER -