Facility Location Models Development To Maximize Total Service Area
AbstractThis 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.
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Bibliographic InfoArticle provided by Research Centre in Public Administration and Public Services, Bucharest, Romania in its journal Theoretical and Empirical Researches in Urban Management.
Volume (Year): 4 (2009)
Issue (Month): 1S (April)
Facility Location; Emergency Facilities; Service Area; Network analysis S.);
Find related papers by JEL classification:
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- O21 - Economic Development, Technological Change, and Growth - - Development Planning and Policy - - - Planning Models; Planning Policy
- R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General
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- 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.
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