Minimum cost polygon overlay with rectangular shape stock panels
This work addresses a specific optimization problem in the construction industry, presenting an incremental analysis of existing algorithms.
The paper tackles the Minimum Cost Polygon Overlay (MCPO) problem, which involves covering a polygon area with rectangular panels, by implementing and comparing three optimization algorithms (greedy search, Monte Carlo, and Genetic Algorithm) to assess their relative effectiveness.
Minimum Cost Polygon Overlay (MCPO) is a unique two-dimensional optimization problem that involves the task of covering a polygon shaped area with a series of rectangular shaped panels. This has a number of applications in the construction industry. This work examines the MCPO problem in order to construct a model that captures essential parameters of the problem to be solved automatically using numerical optimization algorithms. Three algorithms have been implemented of the actual optimization task: the greedy search, the Monte Carlo (MC) method, and the Genetic Algorithm (GA). Results are presented to show the relative effectiveness of the algorithms. This is followed by critical analysis of various findings of this research.