Optimizing Fresh Fruit Display: A Comparative Study of Hybrid Heuristic and Genetic Algorithm for Sustainable Shelf Space Allocation Dyah Satiti, Endah Rahayu Lestari*
Department of Agro-industrial Technology, Faculty of Agricultural Technology, Universitas Brawijaya
Veteran No.10-11, Malang, East Java, Indonesia
*Email: endahlestari24[at]ub.ac.id
Abstract
Reducing postharvest losses while maximizing profit is a critical aspect of sustainable fresh fruit retail management. Fresh fruits are highly perishable and some of them are sensitive to ethylene exposure, which accelerates ripening and spoilage. This study develops and compares two solution approaches for optimizing shelf space allocation and display arrangement in fresh fruit retailing. The first approach integrates a linear programming model with a local heuristic adjustment to prevent ethylene-sensitive fruits from being displayed adjacently. The second approach employs a Genetic Algorithm (GA) as a metaheuristic to handle complex constraints through an evolutionary search process. Numerical experiments are conducted on small and medium problem instances, using actual display space parameters, product space requirements, profit margins, and ethylene sensitivity levels. The results show that the hybrid approach is effective for small-scale configurations but struggles with larger instances due to local optima and feasibility issues. In contrast, the GA consistently generates feasible, near-optimal solutions with higher total expected profit and better space utilization. This research highlights the potential of metaheuristic methods for improving operational decisions in fresh fruit retailing, contributing to reduced waste and extended shelf life. The findings provide practical guidance for retailers seeking to adopt sustainable display strategies that balance profitability and quality preservation.
