PENERAPAN ALGORITMA SEMUT PADA TRAVELING SALESMAN PROBLEM (TSP) UNTUK OPTIMASI JALUR PENGANGKUTAN SAMPAH DI KOTA YOGYAKARTA

Derrida Atsmarotul Ilmi, NIM.: 22106010040 (2026) PENERAPAN ALGORITMA SEMUT PADA TRAVELING SALESMAN PROBLEM (TSP) UNTUK OPTIMASI JALUR PENGANGKUTAN SAMPAH DI KOTA YOGYAKARTA. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

	Text (PENERAPAN ALGORITMA SEMUT PADA TRAVELING SALESMAN PROBLEM (TSP) UNTUK OPTIMASI JALUR PENGANGKUTAN SAMPAH DI KOTA YOGYAKARTA) 22106010040_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf - Accepted Version Download (6MB)
	Text (PENERAPAN ALGORITMA SEMUT PADA TRAVELING SALESMAN PROBLEM (TSP) UNTUK OPTIMASI JALUR PENGANGKUTAN SAMPAH DI KOTA YOGYAKARTA) 22106010040_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf - Published Version Restricted to Registered users only Download (19MB) | Request a copy

Abstract

The Ant Colony System (ACS) algorithm is a method that mimics the behavior of ant colonies in determining the shortest route. This method is used to solve the Traveling Salesman Problem (TSP), which involves finding a route that visits each point exactly once and returns to the starting point. In this study, ACS was applied to determine waste collection routes in Yogyakarta, aiming to minimize the total travel time. The problem was modeled as a TSP on a weighted graph consisting of 14 points, namely 1 Waste Collection Unit (UPS) and 13 waste depots, with the distances between locations represented as edge weights. The algorithm was implemented in four simulations. From these four simulations, the results showed that the simulation without considering truck capacity produced the shortest route, with a total distance of 43.4 km and a travel time of 130 minutes. In contrast, the simulation considering truck capacity resulted in routes divided into multiple trips, with a total distance of 142.9 km and a travel time of 429 minutes. These results indicate that the ACS algorithm can be used as an effective approach for planning waste collection routes, particularly in the Yogyakarta area.

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