Enhancing warehouse efficiency through geographic information system and genetic algorithm

Abstract

Effective warehouse management is crucial for firms to thrive in the global market by facilitating rapid stocking, processing, and delivery of goods while minimizing expenses and improving customer satisfaction. This thesis explores the use of Geographic Information Systems (GIS) and Genetic Algorithms (GA) to improve warehouse operations, such as planning, inventory management, and logistics. The literature study examines the development of warehouse optimization techniques, emphasizing advancements made by GIS and GA. Initially, fuzzy logic-based models enhanced operations by simulating and optimizing warehouse processes. The focus then shifted to improving layouts and order clustering algorithms to boost efficiency. GIS technology has become essential for real-time monitoring, path optimization, and strategic decision-making, enabling precise digital maps and insights into traffic patterns within warehouses. GAs apply natural selection principles to solve optimization issues like route planning and slotting by selecting, merging, and mutating solutions. In warehouse management, GAs enhance product arrangement (slotting) and determine optimal paths for order pickup and delivery. The methodology section details research techniques, data collection, and analysis processes. The warehouse floor layout is digitized using QGIS to create a comprehensive digital model. GA is used for route optimization, reducing travel time and operational expenses, while slotting optimization arranges products to minimize retrieval time and enhance efficiency. The implementation section presents a case study demonstrating the tangible use of GIS technologies in a real warehouse. Benefits include improved routing, reduced trip distances by over 40%, and enhanced productivity. An analysis of 21,020 work orders showed a 1,973.08-kilometer reduction in distance traveled and a 23.3% improvement in operational efficiency. The final section covers research findings and suggests future research. Integrating GIS with GA improves operational efficiency, reduces costs, and increases customer satisfaction. Future research should explore combining GIS with AI and ML for advanced spatial data processing and real-time decision-making. IoT devices can provide real-time warehouse condition reports, while advanced visualization techniques like 3D modeling and augmented reality offer dynamic views of layouts. In summary, combining GIS with GA enhances warehouse management efficiency, offering significant benefits such as increased operational efficiency, reduced expenses, and improved customer satisfaction. This study provides a comprehensive understanding of how spatial technologies can enhance operational effectiveness, encouraging the wider adoption of GIS in the industry.