The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The vehicle routing problem in the electronic commerce environment pays more attention to the time management. This paper established a general mathematical model with the soft time windows in the e-commerce environment. In the process of research, adopted the simulated annealing algorithm for solving it, and analyzed the effect of solutions caused by different importance of distance and time cost...
This study improves the original model of vehicle routing problem by adding some strains such as time windows, volume, weight, as parameters into the model. The model is adjusted to an mutilate-goals vehicle scheduling problem based on the mutilate-goals programming, and study on how the time-windows and time-distinction affects the delivering planning. We use GAMS to simulate and solve this problem.
With the rapid development of electronic commerce, the logistics distribution system brings to the widespread attention. And the agricultural commodity distribution routing (ACDR) optimization is playing the very important role in the agricultural industry. This paper proposed the ant colony optimization (ACO) algorithm to optimize the agricultural commodity distribution routing effectively, which...
In order to solve the logistic distribution vehicle scheduling problem in e-commerce environment, a method was proposed by modifying particle swarm optimization algorithm. In the method, a novel particle presentation for the vehicle scheduling problem was proposed. Simulation results have shown that the algorithm is effective and efficient for the vehicle scheduling problem.
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.