00000ctm a22000003a 4500 UP-8027390931316213353 Buklod 20100923140149.0 a r |||| u| ta 100923s xx d r |||| u| (iLib)UPMIN-00005017243 DLC DLC upmin eng LG93.5 2010 A64 B36 Bangi, Juniejie B. Hybrid invasive weed optimization - particle swarm optimization (IWO-PSO) algorithm for uncapacitated facility location problem. 2010 141 leaves Thesis, Undergraduate (BS Applied Mathematics-Operations Research)- U.P. Mindanao Uncapacitated facility location problem (UFLP) is a mathematical way of selecting the location of uncapacitated facilities such that the total ost of satisfying the demands is minimized. Due to its wide range f applications, several approaches have been developed. In this study, the Hybrid Invasive Weed Optimization - Particle Swarm Optimization (IWO - PSO) algorithm was used in locating the counters of a certain department store. Here, the concept of velocity and position estimation of PSO was embedded to the IWO algorithm making it a better population-based algorithm. One One hundred ten parameter sets were tested to determine which setting best suits the given data. The results showed that higher parameter values have paramount perfornmance in obtainging the best fitness. However, such setting converged slower. Nonetheless, the method succeeded on finding an optimal location of the counters considered in this study. Comparing the generated position of the counters using the algorithm gave better fitness than the current location. Further studies can be made to improved the results such as adding more constraints to the problem and exploring the possibilities to unearth alternatives upon the distribution of the counters. Applying this algorithm to other uncapacitated family location problem would verify its effectiveness in finding the optimal solution. Bio inspiration. Dispersal. Exclusion. Metaheuristic algorithm. Reproduction. Uncapacitated facility location problem. Undergraduate Thesis AMAT200. FI UP UPMIN UPMIN-MAIN LG93.5 2010 A64 B36 Thesis