An optimization approach for an order-picking warehouse: An empirical case

Abstract

Order-picking optimization in a business sustainable competitiveness context is challenging due to prior studies focusing on theoretical model development with unrealistic assumptions in their algorithms and methodological validation, often neglecting practical concerns. This paper improves order-picking operations by employing combinatorial optimization as a travelling salesman problem and class-based dedicated storage models for the ATP company. The paper's originality and novelty lie in bridging the gap between academia and management, presenting an effort to connect theoretical concepts with practical optimization in order-picking warehouse operations in an environment of competitiveness. Realistic data and LINGO software were employed, revealing substantial improvements in the ATP warehouse operations through optimized pick path decisions embedded in warehouse layouts. This paper provides managerial tools for distance traveled optimization in the warehouse that yield competitive edges, enhanced supply chain efficiency and effectiveness, as well as other positive impacts on social, and environmental concerns such as labor safety, customer satisfaction, energy consumption, and CO2 emission. The paper also outlines future research directions to advance warehouse management and address sustainable competitiveness challenges, adding a new dimension to the original research.