Delivery Delay Cost Research Articles

Co-optimization of charging scheduling and platooning for long-haul electric freight vehicles

Freight mileages have been significantly increasing over the past decade, accounting for 11% of global greenhouse gas (GHG) emissions. Freight electrification and platooning are two promising technologies to mitigate the energy and environmental impacts of freight transportation. Effective coordination of charging and platooning are urgently needed to maximize the benefits of these two technologies, especially considering the current inadequate charging infrastructure, long charging duration, higher energy usage, and tight delivery schedules for long-haul electric freight vehicles (EFVs). In this study, we aim to co-optimize the platooning and charging strategies of EFVs. To achieve this goal, we developed a mixed-integer linear programming model to minimize the total system costs, including en-route charging cost, delivery delay cost, and hub charging cost. The proposed model was tested using a case study of a 595-mile Florida interstate highway route and solved by the state-of-the-art branch-and-cut algorithms, through which we demonstrated the effectiveness of using our model to identify the optimal charging and platooning schedules and quantify the spatial distribution of charging demand and platoon energy savings. We also performed sensitivity analyses to better understand the impacts of some critical factors, including the EFV models, charging station (CS) capacity, number of CSs, charging speed, and departure-time windows.

Route Planning for Chain Restaurants With Improved Delivery Mode Using an Adaptive Genetic Algorithm

With the popularization of logistics technology and the improvement of people’s living standards, the number of chain restaurants with delivery service is increasing continuously due to the convenient service and special discounts. However, the inappropriate management mode and delivery delays often lead to high delivery cost, especially during the peak meal period. Therefore, to solve the problems, two delivery modes, Modern Delivery Mode of Chain Restaurants (MDMCR) and Improved Delivery Mode of Chain Restaurants (IDMCR) were first proposed. IDMCR is an one-stage approach to directly solve the delivery routing problem of multiple branches. Furthermore, we presented an adaptive genetic algorithm for delivery of chain restaurants (AGA-DCR) specifically for IDMCR, which adjusts adaptively the traditional crossover and mutation operations to the fitness of individual and population, therefore, local optimal is avoid. The experiments were conducted with the same dataset to compare different approaches. The results demonstrated that AGA-DCR avoided falling into the local optimal while improved the quality of the solution. Moreover, IDMCR combined with AGA-DCR achieved the best performance, reducing the delivery delay cost by 56.2% compared to MDMCR with GA. Additionally, the optimal delivery routes for chain restaurants were visualized to provide a reference solution for the practical applications.

Modeling cost benefit analysis of inspection in a production line

Production management aims to maximize profit by increasing salable output while reducing the cost related with inspection, where inspection is defined as the measurement and quality assessment of items produced. This study is based on a semiconductor production line with consecutive deteriorating machines. Each machine is inspected via the items it produces and an inspection result triggers a machine's repair, if needed. Inspection related cost includes fixed and variable cost of inspection capacity, Yield Loss Cost generated due to unsalable throughput, and delivery delay cost caused by inspection flow-time. The effects of inspection capacity and inspection rate on cost are investigated using analytical and simulation models. Under a given inspection capacity, Yield Loss Cost decreases with growing inspection rate until a minimum is reached, and then starts to increase with further growing rate. This increase is explained by the impact of higher load on the inspection facility, which prolongs the inspection response time. Thus, an optimal inspection rate can be derived for a given inspection capacity. It will be shown that the higher the capacity, the higher the optimal rate, and the lower the yield loss. Determination of optimal inspection capacity considers the capacity cost against the other costs and minimizes the total expected inspection related costs.

Integrating customer responsiveness and distribution cost in designing a two-echelon supply chain network with considering capacity level and piecewise linear cost

When designing supply chains, firms are often faced with the competing demands of improved customer responsiveness and reduced cost. In this paper, we present a two echelon distribution network design problem in supply chain system which includes location, transportation and customer responsiveness decisions. Customer responsiveness is measured by the delivery delay cost. Unlike most of past research, our model allows for multiple levels of capacities available to the distribution centers and piecewise linear transportation cost between suppliers and distribution centers for obtaining economic of scale. A hybrid heuristic combining Tabu search with Simulated Annealing (SA) sharing the same tabu list is developed for solving the problem. We comprise the hybrid algorithm with the optimal solution, Simulated Annealing algorithm and Tabu search algorithm. The results indicate that the method is efficient for a wide variety of problem sizes.

A Basic Study on Defect Inspection Method for ASIC Manufacturing Line (Third Report: A Proposal of Inspection Methodology Based on Chip Cost)

The influence of strict defect control is both the enhancement of manufacturing yield and the delivery delay due to the drop of the machine operation rate. Therefore defect inspection method must be optimized especially for ASIC manufacturing. In the second report, we formularized the inspection parameter dependence on manufacturing yield and machine cleaning cycle that may affect delivery time. In this report, we propose new cost model which can take account of manufacturing yield drop, delivery delay cost etc. The delivery delay cost is based on queuing theory. In the last section of this report, we propose inspection parameter setting methodology to minimize chip cost.