A new method for the selection of distribution centre locations
MetadataShow full item record
This paper investigates the distribution centre location problem with inaccurate information, and a general model based on a rough feasible region is established. By means of synthesizing the believable degree of the rough feasible region and objective functions, a solution model termed as rough multi-objective synthesis effect (RMOSE) model is developed; this constitutes a series of crisp multi-objective programming models that reflect different decision consciousness for each decision maker. The optimal solutions of the RMOSE model can be obtained by using the genetic algorithm, and it is demonstrated that the solution of the RMOSE model in proper parameters is same as that of existing model with fuzzy model information. So the proposed RMOSE model is actually an extension of a crisp multi-objective programming model. Two cases of experiments for the distribution centre location problems show that the proposed method can be directly applied to real world practices and it is better than existing methods with fuzzy model information.
Showing items related by title, author, creator and subject.
Kramer, Annika (2009)Visual perception is our most important sense which enables us to detect and recognise objects even in low detail video scenes. While humans are able to perform such object detection and recognition tasks reliably, most ...
Aizam, Nur Aidya Hanum (2013)Timetabling is a table of information showing when certain events are scheduled to take place. Timetabling is in fact very essential in making sure that all events occur in the time and place required. It is critical in ...
Professional development in HIV prevention education for teachers using flexible learning and tutor supportJackson, Glenda Joy (2004)HIV prevention programs in schools are acknowledged as one of the best prospects for controlling the world HIV epidemic. Epidemiological evidence indicates that deaths world-wide from AIDS are yet to peak. Although HIV ...