Maximum covering location problem to select facility location for operation timbang in the City of Iloilo, Philippines

Abstract

Operation Timbang (OPT) Plus is one of the Philippines’ programs that focuses on nutrition by conducting an annual assessment for 0-59 months old children in barangays to identify the malnutrition data in the area. The barangay is the smallest administrative entity in the Philippines. OPT is a plan of action that estimates the number of malnutrition individuals and identifies those who will get prioritized programs in the community. The Iloilo City Health Office conducted the program in seven districts in the Philippines. The office planned to establish a community centre and playground facility based on the priority/demand areas. Maximum Covering Location Problem (MCLP) is used for this study to determine the optimal location that covers the area. A Mathematical Programming Language (AMPL) is used to apply mathematical programming to the MCLP. The results can be used to identify the optimal facility and the maximum coverage of the demand points. The experiment showed that the facility located in Mandurriao District is the optimal facility location. For Underweight/Severely Underweight children, a maximum total of 646 are covered, and for the Overweight/Obese, 1,041 are covered for the chosen facility. In addition, the findings of the sensitivity analysis indicate that the building of the three facilities in the case study can offer 100 percent of the required coverage area.

Dry Port Location Selection: A Case Study of Tanjung Intan Port

“…The Maximum Coverage Location Problem (MCLP) method or maximum demand covering problem is a mathematical model to solve location-allocation issues with the objective is to maximize the demand met [24]. MCLP modelling can be used to determine the optimal location with a maximum number of limited or predetermined facilities built [25]. Based on Francis et al quoted by Farahani and Hekmatfar [24], MCLP is included in covering problems that can be used in selecting warehouse locations, selecting locations for emergency services, and so on.…”