eprintid: 135740 rev_number: 56 eprint_status: archive userid: 216326 dir: disk0/00/13/57/40 datestamp: 2025-08-26 06:32:22 lastmod: 2025-08-26 06:32:22 status_changed: 2025-08-26 06:32:22 type: thesis metadata_visibility: show creators_name: Gilang Sukma Diriksa, - creators_name: Khusnul Novianingsih, - creators_name: Imam Nugraha Albania, - creators_nim: NIM2106345 creators_nim: NIDN0428117701 creators_nim: NIDN0006048601 creators_id: gilangsukma23@upi.edu creators_id: k_novianingsih@upi.edu creators_id: albania@upi.edu contributors_type: http://www.loc.gov/loc.terms/relators/THS contributors_type: http://www.loc.gov/loc.terms/relators/THS contributors_name: Khusnul Novianingsih, - contributors_name: Imam Nugraha Albania, - contributors_nidn: NIDN0428117701 contributors_nidn: NIDN0006048601 contributors_id: k_novianingsih@upi.edu contributors_id: albania@upi.edu title: PENYELESAIAN MULTIPLE TRAVELING SALESMAN PROBLEM DENGAN TIME WINDOWS MENGGUNAKAN ALGORITMA IMPROVED ANT COLONY OPTIMIZATION ispublished: pub subjects: QA divisions: MAT full_text_status: restricted keywords: Multiple Traveling Salesman Problem dengan Time Windows, Improved Ant Colony Optimization, mutasi reciprocal exchange, local search 2-opt Multiple Traveling Salesman Problem dengan Time Windows, Improved Ant Colony Optimization, reciprocal exchange mutation, 2-opt local search note: ID SINTA Dosen Pembimbing: Khusnul Novianingsih : 258640 Imam Nugraha Albania :6711447 abstract: Multiple Traveling Salesman Problem dengan Time Windows (mTSP-TW) merupakan pengembangan dari TSP dengan melibatkan lebih dari satu salesman dan batasan waktu kunjungan pada setiap lokasi. Penelitian ini menyelesaikan mTSP-TW menggunakan algoritma Improved Ant Colony Optimization (IACO), yang merupakan pengembangan dari ACO dengan penambahan mutasi reciprocal exchange dan local search 2-opt untuk meningkatkan kualitas solusi. Hasil percobaan menunjukkan bahwa IACO mampu menghasilkan solusi yang feasible dan efisien dengan total jarak minimum sebesar 1026,76 km dalam 100 iterasi dan 20 percobaan. Parameter terbaik diperoleh dengan jumlah semut 15, pheromone awal 0,1, tingkat penguapan pheromone 0,2, nilai eksploitasi q₀ = 0,7, serta bobot α = 1 dan β = 2. The Multiple Traveling Salesman Problem dengan Time Windows (mTSP-TW) is an extension of the TSP that involves more than one salesman and time window constraints at each location. This study addresses the mTSP-TW using the Improved Ant Colony Optimization (IACO) algorithm, an enhancement of ACO that incorporates reciprocal exchange mutation and 2-opt local search to improve solution quality. The computational results show that IACO can produce feasible and efficient solutions, achieving a minimum total distance of 1180.50 km in 100 iterations and 20 trials. The best performance was achieved using 15 ants, an initial pheromone value of 0.1, a pheromone evaporation rate of 0.2, an exploitation factor q₀ of 0.7, and pheromone and visibility weights of α = 1 and β = 1, respectively. date: 2025-08-16 date_type: published institution: Universitas Pendidikan Indonesia department: KODEPRODI44201#Matematika_S1 thesis_type: other thesis_name: other official_url: https://repository.upi.edu/ related_url_url: https://perpustakaan.upi.edu/ related_url_type: org citation: Gilang Sukma Diriksa, - and Khusnul Novianingsih, - and Imam Nugraha Albania, - (2025) PENYELESAIAN MULTIPLE TRAVELING SALESMAN PROBLEM DENGAN TIME WINDOWS MENGGUNAKAN ALGORITMA IMPROVED ANT COLONY OPTIMIZATION. S1 thesis, Universitas Pendidikan Indonesia. document_url: http://repository.upi.edu/135740/5/S_MAT_2106345_Title.pdf document_url: http://repository.upi.edu/135740/6/S_MAT_2106345_Chapter1.pdf document_url: http://repository.upi.edu/135740/7/S_MAT_2106345_Chapter2.pdf document_url: http://repository.upi.edu/135740/8/S_MAT_2106345_Chapter3.pdf document_url: http://repository.upi.edu/135740/9/S_MAT_2106345_Chapter4.pdf document_url: http://repository.upi.edu/135740/10/S_MAT_2106345_Chapter5.pdf document_url: http://repository.upi.edu/135740/11/S_MAT_2106345_Appendix.pdf