Um framework para apoiar especialistas na construção de soluções para o problema de manipulação com paletes

Abstract

With high competitiveness in the wholesale and retail sector, the challenge arises of optimizing warehouse management and product handling in pallet racking structures, aiming to reduce operational costs and increase efficiency. Among the problems encountered in this context, the pallet handling problem for wholesale supermarkets (cash and carry) stands out, which seeks to define the allocation for each product, considering the high turnover and variety of Stock Keeping Units. Given the number of optimization algorithms found in the literature, a strategy that enables the construction of solutions is necessary. The objective of this work is to identify an alternative capable of assisting managers in building solutions. Through a literature review, it was possible to observe the need for a generic and easily integrated framework. To verify the framework's behavior, three optimization algorithms (Point-to-Point, Continuous Loop, and Continuous Loop with Buffer), implemented in Python, were integrated. The results showed the solutions found by the techniques and the time spent executing the instances. The framework proved effective for visualizing and analyzing the generated solutions, allowing specialists to monitor each operation clearly and interactively, with a significant reduction in total movements using the Continuous Loop model.