Optimasi Stowage Planning Menggunakan Harris Hawk Optimization dan Rule-Based Expert System

Nur Fatimah, Nabilah Safa (2026) Optimasi Stowage Planning Menggunakan Harris Hawk Optimization dan Rule-Based Expert System. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 5002221041-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (7MB) | Request a copy

Abstract

Perencanaan penyusunan muatan kontainer atau Container Stowage Planning Problem (CSPP) merupakan permasalahan optimasi yang kompleks dan bersifat kombinatorial karena harus mempertimbangkan berbagai batasan operasional dan keselamatan secara simultan. Batasan tersebut meliputi ketentuan penanganan dangerous goods berdasarkan International Maritime Dangerous Goods (IMDG) Code, skenario pelayaran multi-port, serta aspek stabilitas kapal. Ketidaktepatan dalam perencanaan stowage dapat menyebabkan peningkatan biaya operasional, aktivitas container shifting, serta risiko terhadap keselamatan kapal dan muatan. Penelitian ini mengusulkan model optimasi CSPP dengan mengombinasikan Harris Hawks Optimization (HHO) dan Rule-Based Expert System (RBES). HHO digunakan sebagai algoritma optimasi utama untuk menghasilkan konfigurasi penempatan kontainer secara iteratif, sedangkan RBES berperan dalam mengevaluasi kepatuhan solusi terhadap aturan operasional dan keselamatan. Setiap pelanggaran aturan dikonversi menjadi nilai penalti yang diintegrasikan ke dalam fungsi fitness HHO sehingga proses optimasi diarahkan untuk menghasilkan solusi yang layak secara operasional. Pengujian dilakukan menggunakan data kapal kontainer dengan kapasitas muatan 442 TEU dan 3000 kandidat kontainer melalui delapan skenario yang mengevaluasi pengaruh jumlah iterasi, ukuran populasi, internal swap, external replacement, heavy group, dan heavy swap terhadap kinerja algoritma. Hasil eksperimen menunjukkan bahwa konfigurasi terbaik diperoleh pada Skenario VIII yang menggunakan 30 iterasi, ukuran populasi 11, internal swap 25%, external replacement 25%, heavy group 10%, dan heavy swap 25%, dengan nilai fitness sebesar 0.97809. Solusi yang dihasilkan memiliki nilai LCG (Longitudinal Center of Gravity) sebesar −5.53506 × 10−5, TCG (Transverse Center of Gravity) sebesar −1.61686 × 10−17, dan VCG (Vertical Center of Gravity) sebesar 11.528 m yang berada di bawah ambang batas stabilitas sebesar 11,615 m. Hasil tersebut menunjukkan bahwa pendekatan HHO–RBES mampu menghasilkan konfigurasi stowage yang memenuhi aspek operasional dan stabilitas kapal secara efektif.
=====================================================================================================================================
The Container Stowage Planning Problem (CSPP) is a complex combinatorial optimization problem that requires simultaneous consideration of operational and safety constraints. These constraints include the handling of dangerous goods according to the International Maritime Dangerous Goods (IMDG) Code, multi-port voyage operations, and ship stability requirements. Ineffective stowage planning may increase operational costs, container shifting activities, and safety risks for both the vessel and its cargo. This study proposes a CSPP optimization model by integrating Harris Hawks Optimization (HHO) with a Rule-Based Expert System (RBES). HHO is employed as the primary optimization algorithm to iteratively generate container stowage configurations, while RBES evaluates each solution against operational and safety rules. Rule violations are converted into penalty values and incorporated into the HHO fitness function, guiding the optimization process toward operationally feasible solutions. Experiments were conducted using a container ship with a cargo capacity of 442 TEU and 3,000 candidate containers through eight experimental scenarios evaluating the effects of the number of iterations, population size, internal swap, external replacement, heavy group, and heavy swap parameters on the algorithm’s performance. The best performance was achieved in Scenario VIII, which employed 30 iterations, a population size of 11, 25% internal swap, 25% external replacement, 10% heavy group, and 25% heavy swap, yielding a fitness value of 0.97809. The resulting solution produced LCG (Longitudinal Center of Gravity), TCG (Transverse Center of Gravity), and VCG (Vertical Center of Gravity) values of −5.53506×10−5, −1.61686×10−17, and 11.528 m, respectively, with the VCG remaining below the stability threshold of 11.615 m. These results demonstrate that the proposed HHO–RBES approach is capable of generating container stowage configurations that effectively satisfy both operational and ship stability requirements

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Container Stowage Planning Problem, Harris Hawks Optimization, Rule-Based Expert System, Dangerous Goods, Multi-port
Subjects:	Q Science Q Science > QA Mathematics Q Science > QA Mathematics > QA336 Artificial Intelligence
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Nabilah Safa Nur Fatimah
Date Deposited:	04 Aug 2026 02:32
Last Modified:	04 Aug 2026 02:32
URI:	http://repository.its.ac.id/id/eprint/142443

Actions (login required)

View Item