Multi-Objective Optimization for Topological Shipyard Facility Layout using NSGA-II

Abstract

The increasing complexity in ship construction due to larger vessel sizes has placed significant pressure on the shipbuilding industry to enhance efficiency and reduce costs. This paper focuses on optimizing shipyard facility layouts by minimizing material handling costs (MHC) and area costs (AC) using a topological approach for unequal areas. The objective is to develop a layout that reduces these costs while addressing gaps in previous research, which often assumed uniform department sizes. The proposed method employs the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), a heuristic algorithm designed for multi-objective optimization. Unlike previous models, this approach allows for variability in department sizes, aligning more closely with real-world conditions. The layout optimization is conducted by considering adjacency and non-adjacency constraints, ensuring an effective arrangement of shipyard departments. The results demonstrate that the proposed method significantly reduces both MHC and AC, leading to a more efficient and cost-effective shipyard layout. The dual-objective approach not only narrows the gap between topological and geometric models but also optimizes space utilization within the shipyard, making it a practical solution for modern shipbuilding challenges.