Abstract
Previous studies have proposed various frameworks and algorithms to optimize routes to reduce total transportation cost, which accounts for over 29.4% of overall logistics costs. However, it is very hard to find cases in which mathematical models or algorithms are applied to practical business environment cases which require reusable packaging, especially daily operating logistics services like convenience store support systems. Most previous studies have considered developing an optimal algorithm which can solve the mathematical problem within a practical amount of time while satisfying all constraints, such as the capacity of delivery and pick-up, and hard or soft time windows. For daily delivery and pick-up services, like those supporting several convenience stores, it is required to consider the unit transporting the container, as well as the demand, capacity of trucks, travel distance, and traffic congestion. In particular, reusable transport containers and trays should be regarded as important assets of logistics centers. However, if the mathematical model focuses on only satisfying constraints related to delivery and not considering the cost of trays, it is often to leave the empty trays on the pick-up points when there is not enough space in the track. In this study, we propose a mathematical model for optimizing delivery and pick-up plans by extending the general vehicle routing problem of simultaneous delivery and pick-up with time windows, while considering left-over cost. With numerical experiments it has been proved that the proposed model may reduce the total delivery cost. Also, it seems possible to apply the proposed approach to the various logistics businesses which require reusable transport containers like shipping containers, refrigerating containers, trays, and pallets.
Highlights
In response to the rising cost of goods, many companies are committed to minimizing logistics costs through improved logistics processes
In this devising our method there were two factors: (1) the sequence of customers that a vehicle visits; and (2) the number of empty trays picked up from each customer when the vehicle visits. These factors can be merged into a single problem to minimize the total cost, which consists of the travelling cost for visiting customers, the left-over cost which comes from the empty trays not returned from the customers, and penalty cost from the early or late arrivals of vehicles. This problem of vehicle routing can be denoted as VRPSDP-TW-LO, which means the vehicle routing problem in which delivery and pick-up are simultaneously considered with the time window and left-over cost
The current transport management system (TMS) focuses on designing the optimal route, which minimizes the objective function consisting of different factors such as travelling distance, required vehicles, and drivers, while meeting several different constraints, like maximum capacities, time windows to visit, and demand for delivery and pick-up
Summary
In response to the rising cost of goods, many companies are committed to minimizing logistics costs through improved logistics processes. Most previous studies have considered the development of an optimal algorithm which can solve this mathematical problem within a practical timeframe while satisfying all constraints such as the capacity of delivery and pick-up, and time windows. It is very hard to find cases which have applied mathematical models or algorithms to practical business environment cases, especially daily operating logistics services like those serving convenience stores. If the mathematical model focuses on only satisfying constraints related to delivery and does not consider the cost of managing reusable assets, it is often to leave the empty assets at the pick-up points. A vehicle routing problem with simultaneous delivery and pick-up under a time window, considering left over cost (VRPSDP-TW-LO) is proposed.
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