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All Journal International Journal of Business and Management Technology in Society (IJBMTS)
Iwan Vanany
Department of Industrial and System Engineering, Institut Teknologi Sepuluh Nopember
Economics, Econometrics & Finance Social Sciences

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Optimizing Product Delivery through Two-Dimensional Time Warping Demand Allocation under Uncertainty Prita Meilanitasari; Iwan Vanany; Mochamad Nizar Palefi Ma'ady; Nisa Isrofi
International Journal of Business and Management Technology in Society Vol. 2 No. 2: December 2024
Publisher : Direktorat Riset dan Pengabdian Kepada Masyarakat, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j30254256.v2i2.1341

Abstract

Purpose – This study aims to optimize delivery operations by implementing a flexible clustering method to handle demand uncertainty and improve logistics efficiency. Methodology – This study develops a clustering algorithm using a two-dimensional time-warping approach to group demand points based on spatial proximity and demand characteristics. The methodology consists of three stages: 1) processing data on point distances, 2) clustering using two-dimensional time warping, and 3) validating through silhouette analysis. Findings – This study resulted in optimal and efficient demand clustering through location clustering with a Silhouette coefficient value of 0.7 or an accuracy and feasibility level of 70%. The algorithm also shows improved computational efficiency compared to traditional approaches, making it suitable for practical applications in uncertain and dynamic environments. Practical implications – This study holds significant importance for businesses in the logistics and retail sectors. Through demand clustering, businesses can effectively group customer demands and utilize this information to optimize inventory management and delivery solutions.
Co-Authors Mochamad Nizar Palefi Ma'ady Nisa Isrofi Prita Meilanitasari