Giantara, Rangga Etyawan (2026) Multi Objective Production Routing Problem dengan Dimensi Keberlanjutan Menggunakan Algoritma Weighted Tchebycheff Iterated Self Adaptive-Great Deluge (SA-DG) Hyper Heuristic. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Manajemen Rantai Pasok Berkelanjutan (Sustainable Supply Chain Management/SSCM) menuntut integrasi antara efisiensi ekonomi dengan tanggung jawab lingkungan dan sosial. Production Routing Problem (PRP) pada dasarnya berfokus pada minimalisasi biaya, namun tuntutan global telah mengembangkannya menjadi Sustainable Production Routing Problem (SU-PRP). Permasalahan ini didefinisikan sebagai optimasi multiobjektif (Multi-Objective Mixed Integer Linear Programming/MOMILP) yang mencakup tiga tujuan yang saling bertentangan, yaitu meminimalkan biaya ekonomi, biaya emisi CO₂, dan biaya sosial berupa risiko kecelakaan. Kompleksitas model SU-PRP pada skala besar menyebabkan algoritma eksak menjadi kurang efisien, sehingga menjadi motivasi utama penelitian ini. Penelitian bertujuan merumuskan dan mengukur ketiga tujuan keberlanjutan yang saling bertentangan, mengintegrasikan keputusan operasional yang kompleks dan dinamis, serta menghasilkan himpunan solusi Pareto yang komprehensif dan efisien. Tujuan utama penelitian adalah merumuskan model MOMILP SU-PRP yang komprehensif, mengintegrasikan kompleksitas operasional, serta mengembangkan dan menguji algoritma Hyper-heuristic berbasis Weighted Tchebycheff Iterated Self-Adaptive–Great Deluge (SA-GD) untuk penyelesaian masalah skala besar. Model MOMILP diselesaikan menggunakan kerangka Hyper-heuristic dengan pendekatan skalarisasi Weighted Tchebycheff dan strategi pencarian adaptif SA-GD. Luaran yang diharapkan meliputi model matematis MOMILP SU-PRP yang terverifikasi, algoritma Hyper-heuristic Weighted Tchebycheff Iterated SA-GD yang teruji, serangkaian Pareto Optimal Front yang efisien, beragam, dan terdistribusi merata untuk studi kasus skala besar, serta analisis komparatif kinerja algoritma terhadap metode eksak.
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Sustainable Supply Chain Management (SSCM) requires the integration of economic efficiency with environmental and social responsibility. The Production Routing Problem (PRP) traditionally focuses on cost minimization, but increasing global sustainability concerns have extended it into the Sustainable Production Routing Problem (SU-PRP). This problem is formulated as a Multi-Objective Mixed Integer Linear Programming (MOMILP) model with three conflicting objectives: minimizing economic costs, CO₂ emission costs, and social costs associated with accident risk. The complexity of the SU-PRP model for large-scale applications makes exact algorithms computationally inefficient, providing the primary motivation for this research. The study aims to formulate and quantify the three conflicting sustainability objectives, integrate complex and dynamic operational decisions, and generate a comprehensive and efficient set of Pareto-optimal solutions. The main objective is to develop a comprehensive MOMILP model for SU-PRP, incorporate operational complexity, and design and evaluate a Hyper-heuristic algorithm based on the Weighted Tchebycheff Iterated Self-Adaptive Great Deluge (SA-GD) approach for solving large-scale problems. The MOMILP model is solved using a Hyper-heuristic framework with Weighted Tchebycheff scalarization and an adaptive SA-GD search strategy. The expected outputs include a verified MOMILP mathematical model for SU-PRP, a validated Weighted Tchebycheff Iterated SA-GD Hyper-heuristic algorithm, a set of efficient, diverse, and well-distributed Pareto Optimal Fronts for large-scale case studies, and a comparative performance analysis against exact solution methods.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Production Routing Problem (PRP), Multi-Objective Optimization (MOO), Dimensi Keberlanjutan, Hyper-heuristic, Weighted Tchebycheff Production Routing Problem (PRP), Multi-Objective Optimization (MOO), Dimensions of Sustainability, Hyper-heuristic, Weighted Tchebycheff |
| Subjects: | T Technology > T Technology (General) > T57.6 Operations research--Mathematics. Goal programming T Technology > TS Manufactures |
| Divisions: | Interdisciplinary School of Management and Technology (SIMT) > 61101-Master of Technology Management (MMT) |
| Depositing User: | Rangga Etyawan Giantara |
| Date Deposited: | 15 Jul 2026 07:41 |
| Last Modified: | 15 Jul 2026 07:41 |
| URI: | http://repository.its.ac.id/id/eprint/134523 |
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