| dc.description.abstract | In the current market economy conditions, logistics distribution occupies a significant proportion of the overall supply chain, and the expenses related to logistics distribution are continually increasing. As a result, logistics has become a key factor influencing production and distribution costs. Improving the distribution process can help reduce cost wastage and bring positive benefits to the logistics sector. There are several methods to enhance logistics distribution for cost reduction and increased efficiency. Firstly, optimizing route planning and transportation strategies is crucial. Utilizing modern route planning techniques and intelligent transportation systems can ensure the most efficient delivery routes, reducing unnecessary mileage and time wastage. Secondly, adopting energy-saving and environmentally friendly technologies is worth considering. For example, using eco-friendly vehicles and energy-efficient equipment not only reduces fuel consumption and carbon emissions but also saves transportation costs. If Taiwanese logistics operators could introduce mobile smart containers for shipping scheduling, it would not only achieve energy-saving and carbon reduction goals but also reduce related costs such as fuel and labor. Additionally, it could enhance cargo delivery efficiency and mitigate road safety issues caused by conventional trucks and logistics personnel transportation.
This study focuses on the optimization of charging-based mobile smart container shipping scheduling, considering relevant practical constraints, with the objective of minimizing operational costs. A model for the charging-based mobile smart container shipping scheduling is constructed and then solved using the CPLEX mathematical optimization software. However, due to the large scale of the model, the solution time becomes excessively long and impractical. To increase the solution efficiency, this research develops a heuristic algorithm in C++ programming language for testing. To assess the practicality and reliability of this model and algorithm, data from a logistics company in Taoyuan City is used as a testing example. Four heuristic algorithms are developed and compared for testing results, and the optimal heuristic algorithm is selected for sensitivity analysis with different parameters. The research results demonstrate that the proposed model and heuristic algorithm have good performance in practical applications, providing decision-makers with references for optimizing charging-based mobile smart container shipping scheduling. | en_US |