Individual Route Planning for Shoppers

Abstract

Order picking is widely recognized as one of the most labor-intensive and costly ac- tivities in retail and warehouse operations, accounting for over 50% of total operational costs. This thesis addresses the problem of order picking route planning in a retail store environment, modeled as a multi-weighted graph. The primary goal is to design and im- plement a flexible, multi-objective path planning system that balances conflicting criteria: physical travel distance, total time, and the logical ordering of items to manage load. We formalize the store layout as a graph with distinct cost attributes representing "fast" walkways versus "slow" picking aisles. Empirical evaluation via a developed prototype demonstrates how different scalarization strategies enable store managers to optimize for specific operational goals, such as speed or effort minimization.