PENERAPAN ALGORITMA SWEEP DAN MIXED INTEGER LINEAR PROGRAMMING (MILP) UNTUK MENGOPTIMALKAN JADWAL PERAWATAN MESIN SMART WATER STATION (SWS) MENGGUNAKAN MODEL MULTI-TRIP VEHICLE ROUTING PROBLEM (MTVRP) (STUDI KASUS PT XYZ, KABUPATEN BANTUL)

Oktav Berla Perdana, NIM.: 19106060010 (2023) PENERAPAN ALGORITMA SWEEP DAN MIXED INTEGER LINEAR PROGRAMMING (MILP) UNTUK MENGOPTIMALKAN JADWAL PERAWATAN MESIN SMART WATER STATION (SWS) MENGGUNAKAN MODEL MULTI-TRIP VEHICLE ROUTING PROBLEM (MTVRP) (STUDI KASUS PT XYZ, KABUPATEN BANTUL). Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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	Text (PENERAPAN ALGORITMA SWEEP DAN MIXED INTEGER LINEAR PROGRAMMING (MILP) UNTUK MENGOPTIMALKAN JADWAL PERAWATAN MESIN SMART WATER STATION (SWS) MENGGUNAKAN MODEL MULTI-TRIP VEHICLE ROUTING PROBLEM (MTVRP) (STUDI KASUS PT XYZ, KABUPATEN BANTUL)) 19106060010_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf - Published Version Restricted to Registered users only Download (4MB) | Request a copy

Abstract

PT XYZ is one of the companies that provides SWS machines for educational and health institutions in the Special Region of Yogyakarta. In carrying out its business, this company has two operators whose job is to carry out SWS machine maintenance for each customer. Operator schedules and routes made by the company to carry out light maintenance on SWS machines are only based on the estimated shortest distance between customers via Google Maps. Determining the schedule in this way does not guarantee that the schedule implemented by the operator is optimal. Therefore, in this study the sweep and MILP algorithm methods were used with the MTVRP model to produce optimal operator schedules and routes. The MTVRP model is used because one operator can run more than one route as long as it is within the operator's working time constraints. Then, the sweep algorithm method is used to group customers based on the shortest distance and MILP to determine operator routes for each customer group. The purpose of this study, namely to determine the appropriate MTVRP model for optimizing the SWS engine light maintenance schedule, determine the optimal schedule and route to carry out SWS engine light maintenance based on the application of sweep and MILP algorithms, and determine the total time savings needed to carry out light maintenance. SWS machines from the proposed schedule when compared to the company's current schedule. Based on the grouping results using the sweep algorithm, customers are divided into 2 clusters and based on the MILP, routes are generated with the total time required for operators 1 and 2 to carry out light maintenance, respectively for 1035.6 minutes and 1173.8 minutes. Overall, the proposed schedule can reduce the total travel time by 28.64% and the total time needed for light maintenance by 3.67%.

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