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_e _e _aCordenete, Edwin S. _d _b4 _u _c0 _q16 |
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_a _aManila Sports Council Scheduling Model using Monte Carlo simulation / _d _b _n _cEdwin S. Cordenete. _h6 _p |
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_3 _3 _a _d _b _c46 |
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_e _e _c28 cm. _axi, 125 pages _b |
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_b _atext _2rdacontent |
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_3 _30 _b _aunmediated _2rdamedia |
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_3 _30 _b _avolume _2rdacarrier |
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_a _aThesis (M.A.) -- Pamantasan ng Lungsod ng Maynila, 2003.;A directed study presented to the faculty of Graduate School of Engineering in partial fulfillment of the requirements for the degree Master of Engineering Management (MEM) with specialization in Systems Management. _d _b _c56 |
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_b _b _c _aABSTRACT: This directed study is conducted to optimize the utilization of four (4) major sports complexes of the City of Manila handled by Manila Sports Council (MASCO) Office. The main objective of this study is to formulate a new scheduling model for a Manila Sports Council (MASCO) Office, which can optimize the utilization of four major sports complexes. Manila Sports Council was created to provide efficient sports related services to the constituents of Manila. To date, the Office experiences several problems especially on scheduling various indoor sports related activities, games and tournaments utilizing its four major sports complexes. The said sports complexes altogether serves eight hundred ninety-seven (897) user-barangay on a first-come-first-served (FCFS) basis. With this set-up, the researcher wants to solve the following problems: 1. How to maximize the number of indoor sports related activities conducted by various user-barangays in the four major sports complexes of the City? 2. How to minimize the idle time when facility is not in use? Likewise a web-enabled scheduling system was developed to validate real-life applications of the model. Thorough parallel testing and validation are conducted at MASCO Office through the assistance of different personnel directly involved in the scheduling process. The method is experimental simulation. By using experimental simulation design, the researcher comes up with different outputs to analyze Manila Sports Council scheduling system setup. The procedure is patterned after one of the Operations Research Methodologies-simulation modeling. This methodology is best suited especially for complex problems that involve many interacting variables and relationships. This serves to guide a researcher in the effective analysis of factors that must be considered in the making of an OR study. The researcher, based on the gathered data, formulates a scheduling model using the Monte Carlo simulation technique to visualize the flow and optimize the utilization of four major sports complexes. By identifying office requirements and by gathering all necessary data in scheduling model design, the researcher is able to make simulation experiments for MASCO scheduling model. After ten replications of simulation experiments, an average of 296 user-barangays (or 74 user-barangays per sport complex) can be accommodated with a 99.77% utilization percentage. This means that the model increases the number of user-barangays that can be accommodated thereby optimizing the usage of the sports complexes. Idle time of sports complex utilization is reduced from an average of forty (40%) percent to approximately less than five (5%) percent. Based on the simulation experiments and web-enabled scheduling system developed, the following conclusions are drawn: 1. The number of sports activities from various user-barangays that can be accommodated is increased from an average of 64 user-barangays to 296 user-barangays in the new scheduling model using simulation technique. 2. The percentage of idle time (i.e., facility is not in use) is reduced from forty (40%) percent to approximately less than five (5%) percent in the optimization process. 3. The utilization of the four major sports complexes can be further optimized with the aid of the web-enabled scheduling and reservation system developed in this study. The researcher finally offers several related recommendations for future research studies. _u |
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