Pengembangan Model Rute Distribusi Dinamis untuk Multi-Temperature Perishable Product dengan Memperhatikan Biaya Energi Pendinginan

Wardana, Nikolas Pradipta (2026) Pengembangan Model Rute Distribusi Dinamis untuk Multi-Temperature Perishable Product dengan Memperhatikan Biaya Energi Pendinginan. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pertumbuhan logistik rantai dingin dan layanan quick commerce menuntut model distribusi yang mampu menangani pesanan dinamis tanpa mengabaikan kesegaran produk dan biaya energi pendinginan. Penelitian terdahulu umumnya hanya mengintegrasikan sebagian aspek dan belum memadukan dinamika permintaan, kompatibilitas multi-suhu, serta biaya energi pendinginan berbasis termodinamika dalam satu kerangka terpadu. Penelitian ini mengembangkan model Dynamic Vehicle Routing Problem multi-suhu dengan fungsi tujuan lima komponen, yaitu biaya kehilangan kesegaran berbasis peluruhan Arrhenius, biaya tetap kendaraan, biaya perjalanan, biaya energi pendinginan yang mengintegrasikan lima sumber beban kalor, dan penalti penolakan pesanan. Model diselesaikan menggunakan algoritma Variable Neighborhood Descent dalam kerangka rolling horizon dengan mekanisme cheapest insertion untuk menangani pesanan dinamis. Validasi model dilakukan melalui perbandingan sistematis terhadap praktik konvensional VRP statis. Hasil eksperimen membuktikan bahwa ketiga dimensi utama model (dinamika pesanan, multi-suhu, dan biaya pendinginan termodinamik) saling melengkapi dan tidak dapat dipisahkan. Algoritma usulan secara efektif mampu menyerap ketidakpastian pesanan dinamis hingga performanya mendekati kondisi ideal dengan informasi-penuh. Lebih lanjut, pemodelan termodinamika terbukti sangat krusial, khususnya pada iklim tropis bersuhu tinggi dan komoditas beku (frozen), di mana pengabaian aspek fisis ini terbukti mengakibatkan kegagalan operasional dan lonjakan biaya yang ekstrem. Secara keseluruhan, analisis mengkonfirmasi bahwa tingkat dinamisme permintaan dan besaran denda penolakan merupakan faktor penentu paling dominan terhadap total biaya distribusi.
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The growth of cold chain logistics and quick commerce services demands distribution models capable of handling dynamic orders without neglecting product freshness and refrigeration energy cost. Prior studies have generally integrated only partial aspects and have not combined demand dynamism, multi-temperature compatibility, and thermodynamics-based refrigeration energy cost within a single unified framework. This study develops a multi-temperature Dynamic Vehicle Routing Problem model with a five-component objective function, namely freshness-loss cost based on Arrhenius decay, fixed vehicle cost, travel cost, refrigeration energy cost integrating five heat-load sources, and order-rejection penalty. The model is solved using a Variable Neighborhood Descent algorithm within a rolling horizon framework with a cheapest insertion mechanism to handle dynamic orders. Validation was conducted through a systematic comparison against conventional static VRP practices. Experimental results prove that the three core dimensions of the model (dynamism, multi-temperature, and thermodynamic refrigeration costs) are complementary and indispensable. The proposed algorithm effectively absorbs the uncertainty of dynamic orders, achieving a performance level that closely approximates ideal full-information conditions. Furthermore, thermodynamic modeling proves critical, particularly in high-temperature tropical climates and for frozen commodities, where neglecting this physical aspect leads to operational failure and extreme cost spikes. Overall, the analysis confirms that the degree of demand dynamism and the rejection penalty are the most dominant determinants of total distribution costs.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Biaya Energi Pendinginan, Distribusi Multi-Suhu, Dynamic Vehicle Routing Problem, Produk Perishable, Variable Neighborhood Descent
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management Q Science > Q Science (General) > Q180.55.M38 Mathematical models T Technology > T Technology (General) > T57.6 Operations research--Mathematics. Goal programming T Technology > T Technology (General) > T58.62 Decision support systems T Technology > TP Chemical technology > TP370 Food processing and manufacture
Divisions:	Faculty of Industrial Technology > Industrial Engineering > 26201-(S1) Undergraduate Thesis
Depositing User:	Nikolas Pradipta Wardana
Date Deposited:	30 Jul 2026 07:25
Last Modified:	30 Jul 2026 16:22
URI:	http://repository.its.ac.id/id/eprint/139904

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