Facility Location Models Development To Maximize Total Service Area
This paper present and discuss the new developed model to maximize total service area of a fixed number of facilities. Two greedy algorithms, Greedy Adding (ADD) and Greedy Adding with Substitution (GAS), were applied to solve the optimization problem of the Maximal Service Area Problem (MSAP). The MSAP is a discrete model where a specified number of facilities that achieve the best objective function value of the model are selected out of a finite set of candidate sites. In this study the determination of Fire stations location in Jakarta Selatan, Indonesia, were chosen for simulation. The shape of total service area covered by emergency facilities such as fire stations and ambulances is influenced by the road accessibility. The determination process requires lots of manual intervention in trying to improve the total service area. The two algorithms managed to reach better coverage than the coverage of existing fire stations with the same number of fire stations within the same travel time. The ADD managed to reach the coverage of 82.81% and GAS did 83.20%., while the existing fire stations only reach 73.69%.w. The approach undertaken in conventional facility location models had only defined a facility’s service area simply by a circular coverage. And therefore, it can be concluded that, as such the conventional approach is appropriate for facilities which are not influenced by topographical and road network barriers.
Volume (Year): 4 (2009)
Issue (Month): 1S (April)
|Contact details of provider:|| Postal: 6 ROMANA PLACE, 70167 - BUCHAREST|
Web page: http://ccasp.ase.ro/
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Klose, Andreas & Drexl, Andreas, 2005. "Facility location models for distribution system design," European Journal of Operational Research, Elsevier, vol. 162(1), pages 4-29, April.
When requesting a correction, please mention this item's handle: RePEc:rom:terumm:v:4:y:2009:i:1s:p:87-100. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Colesca Sofia)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.