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PENERAPAN ALGORITMA NAWAZ ENSCORE HAM KALCZYNSKI AND KAMBUROWSKI (NEHKK1) PADA PENJADWALAN PRODUKSI DI PT X Fran Setiawan; Yani Herawati; Terry Indrayadi Tjokro
INDUSTRIAL ENGINEERING JOURNAL of the UNIVERSITY of SARJANAWIYATA TAMANSISWA Vol 2 No 2 (2018)
Publisher : Teknik Industri Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/iejst.v2i2.4459

PT X merupakan perusahaan yang bergerak di bidang industri handuk yang berlokasi di Bandung, Jawa Barat. Perusahaan ini memproduksi empat tipe handuk yaitu handuk jumbo, standar, tanggung dan kecil. Masalah yang dihadapi oleh PT X adalah ketidakmampuan kepala produksi dalam mengestimasi waktu penyelesaian pesanan konsumen dengan tepat sehingga sering terjadi keterlambatan pengiriman pesanan kepada konsumen. Penelitian ini bertujuan untuk membantu kepala produksi PT X dalam mengestimasi waktu penyelesaian pesanan dengan tepat sehingga waktu penyelesaian pesanan konsumen sesuai dengan yang dijanjikan oleh kepala produksi PT X dengan mengusulkan suatu sistem penjadwalan produksi. Penjadwalan produksi yang diusulkan adalah penjadwalan produksi flowshop dengan algoritma Nawaz Enscore Ham Kalcynski and Kamburowski (NEHKK1) dan membuat alat bantu penjadwalan berbasis algoritma NEHKK menggunakan Microsoft Excel Visual Basic. Algoritma NEHKK1 merupakan hasil dari penyempurnaan algoritma NEH. Algoritma ini telah diakui sebagai metode yang paling baik dalam meminimasi makespan untuk permutation flow-shop. Sistem penjadwalan yang diusulkan kemudian diterapkan pada data historis perusahaan dan berhasil menurunkan keterlambatan sebesar 40%.Â Kata Kunci: Â penjadwalan produksi, permutation flow shop, nawaz enscore ham, NEHKK1

On Modelling and Solving Heterogeneous Vehicle Routing Problem with Multi-Trips and Multi-Products Fran Setiawan; Nur Aini Masruroh; Zita Iga Pramuditha
Jurnal Teknik Industri Vol. 21 No. 2 (2019): December 2019
Publisher : Institute of Research and Community Outreach - Petra Christian University

Vehicle routing problem (VRP) is a model to determine an optimal routing plan for a fleet of homogeneous vehicles to serve a set customer which some operational constraints are satisfied. In most practical distribution problems, customer demands are served using heterogeneous fleet of vehicles. This kind of VRP is called Heterogeneous Vehicle Routing Problem (HVRP). HVRP has evolved into a rich research area because of its practical. There were many studies of rich extensions of the standar HVRP. This research aims to enrich the extentions of HVRP which is motivated by real case in one of pharmacy distribution company in Indonesia which is delivered multi-products to its 55 customers by allowing some vehicles which has small capacity to perform multi-trips. This problem is called Heterogeneous Vehicle Routing Problem with Multi-Trips and Multi-Products (HVRPMTMP).The mixed integer linear programming is developed based on four-index vehicle flow formulation. The model can be used generally in the same context of distribution problem. HVRPMTMP is generally NP-Hard problem, so the computational time using branch and bound in LINGO 16.0 is increasing exponentially by increasing the number of customers. Genetic algorithm is proposed to solve the real case. The result of the proposed GA can reduce the total cost from Rp 352540.6,- to Rp 180555,- or 48.78% from the current company policy.

The Supply Chain Integrated Inventory Model for Single Product, Multi-Buyer and Multi-Vendor Kinley Aritonang; Cynthia Prithadevi Juwono; Cherish Rikardo; Fran Setiawan; Adrianus Vincent Djunaidi
International Journal of Supply Chain Management Vol 9, No 6 (2020): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

Show Abstract | Download Original | Original Source | Check in Google Scholar

This paper presents an extended integrated inventory model with multi vendors that produce one item product and supply it to multi buyers. It is assumed that vendor production rates are not equal and the demands of buyers assumed to be normally distributed and independent. The model formulation was made for each buyer and vendor. Then, each cost component from the buyer and vendor is combined to form the total inventory costs. This model uses the service level as constraint. The final mathematical model consists of formulations of the total inventory costs and with certain service level.

Application of Genetic Algorithms to Solve MTSP Problems with Priority (Case Study at the Jakarta Street Lighting Service) Sugih Sudharma Tjandra; Fran Setiawan; Hanoum Salsabila
Jurnal Optimasi Sistem Industri Vol. 21 No. 2 (2022): Published in November 2022
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v21.n2.p75-86.2022

Transportation is one thing that is very important and is the highest cost in the supply chain. One way to reduce these costs is to optimize vehicle routes. The Multiple Traveling Salesman Problem (MTSP) and Capacitated Vehicle Routing Problem (CVRP) are models that have been extensively researched to optimize vehicle routes. In its development based on actual events in the real world, some priorities must be visited first in optimizing vehicle routes. Several studies on MTSP and CVRP models have been conducted with exact solutions and algorithms. In a real case in the Jakarta City Street Lighting Section, the problem of determining the route in three shifts is a crucial problem that must be resolved to increase worker productivity to improve services. Services in MCB (Miniature Circuit Breaker) installation and maintenance activities for general street lights and priority is given to light points that require replacement. Because, in this case, the delivery capacity is not taken into account, the priority of the lights visited is random, and the number of street light points is enormous, in this study, we use the MTSP method with priority and solve by a genetic algorithm assisted by the nearest neighbor algorithm. From the resolution of this problem, it was found that the travel time reduction was 32 % for shift 1, 24 % for shift 2, and 23 % for shift 3. Of course, this time reduction will impact worker productivity so that MCB installation can be done faster for all lights and replace a dead lamp.

Application of Genetic Algorithms to Solve MTSP Problems with Priority (Case Study at the Jakarta Street Lighting Service) Sugih Sudharma Tjandra; Fran Setiawan; Hanoum Salsabila
Jurnal Optimasi Sistem Industri Vol. 21 No. 2 (2022): Published in October 2022
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v21.n2.p75-86.2022

Transportation is one thing that is very important and is the highest cost in the supply chain. One way to reduce these costs is to optimize vehicle routes. The Multiple Traveling Salesman Problem (MTSP) and Capacitated Vehicle Routing Problem (CVRP) are models that have been extensively researched to optimize vehicle routes. In its development based on actual events in the real world, some priorities must be visited first in optimizing vehicle routes. Several studies on MTSP and CVRP models have been conducted with exact solutions and algorithms. In a real case in the Jakarta City Street Lighting Section, the problem of determining the route in three shifts is a crucial problem that must be resolved to increase worker productivity to improve services. Services in MCB (Miniature Circuit Breaker) installation and maintenance activities for general street lights and priority is given to light points that require replacement. Because, in this case, the delivery capacity is not taken into account, the priority of the lights visited is random, and the number of street light points is enormous, in this study, we use the MTSP method with priority and solve by a genetic algorithm assisted by the nearest neighbor algorithm. From the resolution of this problem, it was found that the travel time reduction was 32 % for shift 1, 24 % for shift 2, and 23 % for shift 3. Of course, this time reduction will impact worker productivity so that MCB installation can be done faster for all lights and replace a dead lamp.

Pengembangan Model Optimasi Tangguh Time-Dependent Travel Times Vehicle Routing Problem Fran Setiawan; Carles Sitompul
Jurnal PASTI (Penelitian dan Aplikasi Sistem dan Teknik Industri) Vol 19, No 3 (2025): Jurnal PASTI
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/pasti.2025.v19i3.004

Peningkatan laju urbanisasi dan perkembangan teknologi internet membuat permintaan kegiatan pengangkutan barang di kota besar semakin banyak. Hal ini menyebabkan berbagai permasalahan di kota, salah satunya yaitu kemacetan lalu lintas. Permasalahan-permasalahan ini mendorong munculnya konsep logistik perkotaan. Model vehicle routing problem (VRP) merupakan model utama untuk mengatasi permasalahan operasional distribusi barang. Salah satu cara untuk mengurangi kemacetan adalah membatasi pengantaran barang di jam-jam sibuk. Varian dari VRP yang dapat mengakomodasi ini adalah time-dependent vehicle routing problem (TDVRP) yang mempertimbangkan variasi dari waktu tempuh sepanjang hari dengan membagi jam per hari menjadi beberapa interval waktu sehingga waktu tempuh kendaraan disuatu interval waktu berbeda dengan interval waktu yang lainnya. Penelitian ini mengembangkan model TDVRP yang mengakomodasi ketidakpastian pada waktu tempuh dengan menggunakan pendekatan optimasi tangguh. Pengujian model dilakukan dengan bantuan software AMPL. Hasil pengujian menunjukkan bahwa rata-rata total waktu tempuh model tangguh meningkat sekitar 2–3% dibandingkan model deterministik, namun variasi antar skenario sekitar 5%, yang menunjukkan tingkat ketangguhan dan kestabilan hasil yang baik terhadap ketidakpastian. Dengan demikian, model tangguh mampu memberikan solusi yang lebih andal untuk sistem logistik perkotaan.

Pengembangan Model Optimasi Tangguh Time-Dependent Travel Times Vehicle Routing Problem Fran Setiawan; Carles Sitompul
Jurnal PASTI (Penelitian dan Aplikasi Sistem dan Teknik Industri) Vol. 19 No. 3 (2025): Jurnal PASTI
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/pasti.2025.v19i3.004

Peningkatan laju urbanisasi dan perkembangan teknologi internet membuat permintaan kegiatan pengangkutan barang di kota besar semakin banyak. Hal ini menyebabkan berbagai permasalahan di kota, salah satunya yaitu kemacetan lalu lintas. Permasalahan-permasalahan ini mendorong munculnya konsep logistik perkotaan. Model vehicle routing problem (VRP) merupakan model utama untuk mengatasi permasalahan operasional distribusi barang. Salah satu cara untuk mengurangi kemacetan adalah membatasi pengantaran barang di jam-jam sibuk. Varian dari VRP yang dapat mengakomodasi ini adalah time-dependent vehicle routing problem (TDVRP) yang mempertimbangkan variasi dari waktu tempuh sepanjang hari dengan membagi jam per hari menjadi beberapa interval waktu sehingga waktu tempuh kendaraan disuatu interval waktu berbeda dengan interval waktu yang lainnya. Penelitian ini mengembangkan model TDVRP yang mengakomodasi ketidakpastian pada waktu tempuh dengan menggunakan pendekatan optimasi tangguh. Pengujian model dilakukan dengan bantuan software AMPL. Hasil pengujian menunjukkan bahwa rata-rata total waktu tempuh model tangguh meningkat sekitar 2–3% dibandingkan model deterministik, namun variasi antar skenario sekitar 5%, yang menunjukkan tingkat ketangguhan dan kestabilan hasil yang baik terhadap ketidakpastian. Dengan demikian, model tangguh mampu memberikan solusi yang lebih andal untuk sistem logistik perkotaan.

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