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Pengembangan Algoritma Hybrid Metaheuristik Untuk Penentuan Rute Pengiriman Produk Perishable Trihardani, Luki; Candra Dewi, Oki Anita
Jurnal Teknik Industri Vol 18, No 2 (2017): Agustus
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

The decision to dispatch consumers demand has become a strategic and tactical consideration to be solved in an integrated manner. In this study, the problem of determining routing problem take case study of delivery of perishable product. The routes determination should take into account the unique characteristics of perishable products possess. Perishable products continuously decreases quality over their lifetime. The challenge for distributors is how to minimize the cost of delivering perishable products by taking into account the temperature so that it can serve a number of customers within the specified timeframe,The problem of determining the route on delivery is included in the combinatorial optimization problem, thus causing this problem to be complex to be solved by the exact method. On the other hand, metaheuristic methods are increasingly being developed to be applied in the completion of combinatorial optimizations.This research started from mathematical model of perishable product delivery which pay attention to perishability (quality, temperature, quality loss) and time windows. Based on this model, this research develops the route settlement algorithm of delivery of perishable product using metaheuristic, particle swarm optimization. The algorithm development is required because route determination included in discrete issues. In addition, the development of algorithms to improve performance by combining (hybrid) algorithms, nearest neighbor and particle swarm optimization. Experiments were performed on 2 sets of Solomon data. From the experimental results with the metaheuristic hybrid algorithm is able to provide better performance than pure metaheuristik. Although the solution gap produced by these two algorithms is not very significant, but when viewed from the computation time and the number of iterations required to find the best solution, this metaheuristic hybrid algorithm can save an average time of 17 times from pure metaheuristic algorithm.

HOW HALAL TRANSPORTATION SYSTEM IMPACT THE LOCATION ROUTING PROBLEM Oki Anita Candra Dewi; Luki Trihardani
Journal of Engineering and Management in Industrial System Vol 5, No 1 (2017)
Publisher : Badan Penerbit Jurnal, Faculty of Engineering, Universitas Brawijaya

Halal products become more popular in the world market today that increase the demand of other halal services especially in halal distribution system. These services are designed not only for profitability but its ability to serve customers to maintain the integrity of their halal products. The important decision of designing halal distribution system is determining the location of facilities. In this paper, a halal and non-halal demand constrains with vehicle flow formulation of an uncapacitated location routing model is presented. Halal and non-halal goods are not mixed on a same transportation vehicle. Its a clear difference in transportation of halal and non-halal goods. A location routing problem used to minimize total cost simultaneously. A heuristic algorithm is developed to solve minimum cost considering halal aspect. This paper conduct some numerical experiments to show the behavior of this algorithm.

Pengembangan Algoritma Hybrid Metaheuristik Untuk Penentuan Rute Pengiriman Produk Perishable Luki Trihardani; Oki Anita Candra Dewi
Jurnal Teknik Industri Vol. 18 No. 2 (2017): Agustus
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol18.No2.191-206

The decision to dispatch consumers demand has become a strategic and tactical consideration to be solved in an integrated manner. In this study, the problem of determining routing problem take case study of delivery of perishable product. The routes determination should take into account the unique characteristics of perishable products possess. Perishable products continuously decreases quality over their lifetime. The challenge for distributors is how to minimize the cost of delivering perishable products by taking into account the temperature so that it can serve a number of customers within the specified timeframe,The problem of determining the route on delivery is included in the combinatorial optimization problem, thus causing this problem to be complex to be solved by the exact method. On the other hand, metaheuristic methods are increasingly being developed to be applied in the completion of combinatorial optimizations.This research started from mathematical model of perishable product delivery which pay attention to perishability (quality, temperature, quality loss) and time windows. Based on this model, this research develops the route settlement algorithm of delivery of perishable product using metaheuristic, particle swarm optimization. The algorithm development is required because route determination included in discrete issues. In addition, the development of algorithms to improve performance by combining (hybrid) algorithms, nearest neighbor and particle swarm optimization. Experiments were performed on 2 sets of Solomon data. From the experimental results with the metaheuristic hybrid algorithm is able to provide better performance than pure metaheuristik. Although the solution gap produced by these two algorithms is not very significant, but when viewed from the computation time and the number of iterations required to find the best solution, this metaheuristic hybrid algorithm can save an average time of 17 times from pure metaheuristic algorithm.

Prediksi dan Optimasi Kekasaran Permukaan pada Proses Pemesinan Menggunakan Support Vector Regression Rohman, Muhamad Nur; Hartanti, Lusia Permata Sari; Trihardani, Luki
Widya Teknik Vol. 24 No. 2 (2025): November
Publisher : Fakultas Teknik, Universitas Katolik Widya Mandala Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33508/wt.v24i2.7373

Abstract: Tuntutan terhadap efisiensi energi dan pengurangan dampak negatif lingkungan dalam proses manufaktur mendorong perlunya pendekatan yang lebih cerdas dan berkelanjutan dalam pengendalian kualitas. Studi ini bertujuan untuk membangun model prediktif berbasis Support Vector Regression (SVR) dan mengintegrasikannya dengan algoritma optimasi Equilibrium Optimizer (EO) guna memprediksi dan mengoptimalkan parameter pemesinan pada proses bubut baja AISI 1045. Pemodelan dengan SVR berbasis data eksperimen dengan tiga parameter input yaitu kecepatan potong (v), laju pemakanan (f), dan kedalaman potong (d), dan kekasaran permukaan (Ra) sebagai output. Hasil analisis ANOVA menunjukkan bahwa laju pemakanan dan kecepatan potong merupakan parameter signifikan yang mempengaruhi nilai kekasaran permukaan, sedangkan kedalaman potong tidak berpengaruh signifikan. Model SVR yang dikembangkan menunjukkan performa prediksi yang sangat baik dengan nilai Mean Absolute Percentage Error (MAPE) yang rendah dan koefisien determinasi (R²) yang tinggi, baik pada data pelatihan maupun pengujian. Validasi visual melalui scatter plot juga menunjukkan kecocokan yang sangat baik antara data prediksi dan data eksperimen. Simulasi berbasis model SVR, yang divisualisasikan melalui surface plot, tidak hanya mengonfirmasi temuan dari ANOVA tetapi juga mampu mengungkapkan interaksi tersembunyi antar parameter, seperti pengaruh simultan antara kecepatan potong dan kedalaman potong terhadap kekasaran permukaan. Optimasi lebih lanjut menggunakan kombinasi SVR-EO berhasil menemukan parameter pemesinan optimal, yakni v = 143.92 m/menit, f = 0.12 mm/rev., dan d = 0,7 mm, yang menghasilkan nilai Ra = 1,244 µm—lebih rendah dari nilai terbaik eksperimen. Hasil ini membuktikan bahwa pendekatan SVR-EO efektif untuk meningkatkan kualitas, efisiensi, dan keberlanjutan dalam proses pemesinan, serta mencerminkan nilai profesionalisme dalam penerapan teknologi cerdas untuk mendukung praktik manufaktur berkelanjutan.

Humanitarian Logistics Optimization for Flood Preparedness: An Integrated Model for Post-Aids Allocation Trihardani, Luki; Sabilarrozak, Billy Maulana; Erdiansyah, Sandra Ravi
Science Tech: Jurnal Ilmu Pengetahuan dan Teknologi Vol 11 No 2 (2025): August
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/st.vol11.no2.a19282

Flooding continues to pose a major challenge in urban areas of developing countries, necessitating effective humanitarian logistics, particularly during the preparedness phase. However, the absence of an optimized aid post-placement strategy remains a significant barrier to efficient aid distribution. This study presents a humanitarian logistics preparedness model that integrates K-means clustering with the Set Covering Location Problem (SCLP) to enhance aid post allocation. The clustering technique categorizes affected areas based on geographical proximity and flood severity, ensuring a more effective resource distribution. Compared to traditional district-based grouping, the proposed approach improves resource allocation efficiency by 5.61%. The model was tested using Excel Solver under varying disaster impact scenarios. Findings indicate that in the 100% affected scenario, 37 villages were covered by 18 aid posts, with round-trip distance of 74.72 km. In the 50% affected scenario, 19 villages were served by 8 aid posts, with the distance reduced to 33.65 km. The results highlight the importance of integrating clustering techniques with optimization models to improve data-driven humanitarian logistics planning. The proposed framework facilitates systematic aid distribution, making it a scalable solution that can be adapted to other disaster-prone regions to strengthen flood disaster response strategies

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