Metaheuristic for the Multiple Level Warehouse Layout Problem

In this paper, we introduce an ant colony optimization (ACO) algorithm for solving the NP-hard Multiple Level Warehouse Layout Problem (MLWLP). The problem description consists of a warehouse made up of several levels, each divided into a known number of cells, and different product types need to be allocated while respecting the capacity constraints. There is one I/O port located at different horizontal distances from each cell, and the objective is to minimize the total horizontal and vertical costs. The ACO comprises two stages, and its performance is evaluated by comparing its solutions to that of Branch and Bound (B&B) and Genetic Algorithm (GA). Experimental results show that ACO attains optimal solutions for small problems, and superior solutions to B&B and GA for larger problems.