Flood Facility Location-Allocation in Marikina City Using MCLP with Lagrange  

Oleh:

Santos, Mary Gold ; Meriño, Madelyne ; Sore, Nestley ; Quevedo, Venusmar C.

Jenis: Article from Proceeding
Dalam koleksi: The 14th Asia Pacific Industrial Engineering and Management Systems Conference (APIEMS), 3-6 December 2013 Cebu, Philippines, page 1-13.
Topik: Facility Location Problem; Lagrange; evacuation; flood; disaster management; Maximal Covering Location Problem (MCLP)
Fulltext: 2017.pdf (575.98KB)

Isi artikel

Shelter location-allocation for evacuation planning is an effective pre-impact tool for reducing the threat from the hazard; when predictions are not feasible in cases like fires or floods, evacuation still serves a variety of emergency functions as a post-impact measure. Evacuation operation, a process of relocating residents from any dangerous sites to safer destination in the shortest possible time, is of prime importance in emergency management. Untimely assistance, poor quality of services and facilities have always been the major problem in evacuation centers during disasters. Evacuation planning is important in disaster emergency management and homeland defense preparation. Traditional evacuation warning systems simply convey the threat descriptions and the need for evacuation to the affected population via mass media communication or alarm systems. This study used MCLP with Lagrange optimization model based from Lee and Yang to optimize the number of strategic locations by relaxing constraints in order to obtain the optimal demand coverage for every facility location. The model was solved using MS Office Excel Premium Solver Pro which yield five (5) potential sites strategically located that can cover three hundred two thousand thirty one (302, 031) people or seventy one percent (71%) of the total population in Marikina. Significant factors were considered in improving the effectiveness of potential facility locations. Mitigation projects and sound engineering solutions to reduce the impact of disasters are recommended.

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