The maximal covering location problem with capacities on total workload
Management Science
On the use of genetic algorithms to solve location problems
Computers and Operations Research - Location analysis
Genetic subgradient method for solving location-allocation problems
Applied Soft Computing
Solution approaches for facility location of medical supplies for large-scale emergencies
Computers and Industrial Engineering
Joint location and dispatching decisions for Emergency Medical Services
Computers and Industrial Engineering
Efficiency evaluation for allocating community-based health services
Computers and Industrial Engineering
Computers and Electronics in Agriculture
Determination of the locations and capacities of sugar cane loading stations in Thailand
Computers and Industrial Engineering
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Malaysia has seen tremendous growth in the standard of living and household per capita income. The demand for a more systematic and efficient planning has become increasingly more important, one of the keys to achieving a high standard in healthcare. In this paper, a Maximal Covering Location Problem (MCLP) is used to study the healthcare facilities of one of the districts in Malaysia. We address the limited capacity of the facilities and the problem is formulated as Capacitated MCLP (CMCLP). We propose a new solution approach based on genetic algorithm to examine the percentage of coverage of the existing facilities within the allowable distance specified/targeted by Malaysian government. The algorithm was shown to generate good results when compared to results obtained using CPLEX version 12.2 on a medium size problem consisting of 179 nodes network. The algorithm was extended to solve larger network consisting of 809 nodes where CPLEX failed to produce non-trivial solutions. We show that the proposed solution approach produces significant results in determining good locations for the facility such that the population coverage is maximized.