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A Smart Logistics information and analytics system for last-mile delivery optimisation

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Parent Category: 2026

Category: Content №3 2026

Created on 26 June 2026

Last Updated on 26 June 2026

Published on 30 November -0001

Written by O. Lyashuk, D. Ilyassov, L. Matiichuk, D. Mironov, R. Gloviak

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Authors:

O. Lyashuk, orcid.org/0000-0003-4881-8568, Ternopil Ivan Puluj National Technical University, ­Ternopil, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

D. Ilyassov*, orcid.org/0000-0001-6150-6492, Turan University, Higher School of Marketing and Logistics, Almaty, Republic of Kazakhstan, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

L. Matiichuk, orcid.org/0000-0001-6701-4683, Ternopil Ivan Puluj National Technical University, Ternopil, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

D. Mironov, orcid.org/0000-0002-5717-4322, Ternopil Ivan Puluj National Technical University, ­Ternopil, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

R. Gloviak, orcid.org/0009-0000-3987-9516, Ternopil Ivan Puluj National Technical University, ­Ternopil, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2026, (3): 155 - 165

https://doi.org/10.33271/nvngu/2026-3/155

Abstract:

Purpose. To develop a Smart Logistics information and analytics system that supports decision-making in last-mile delivery optimisation and logistics partner selection based on operational data analysis and multi-criteria evaluation of service quality.

Methodology. An integrated approach is proposed that combines a microservice architecture, rule-based decision logic, geospatial services and multi-criteria optimisation methods. To aggregate heterogeneous carrier performance indicators (SLA, delivery price and NPS), the generalised Harrington desirability function is applied, enabling indicators of different nature to be transformed into a unified evaluation scale.

Findings. The architecture and operational algorithms of the Smart Logistics system were developed to support automated carrier selection and personalised delivery decisions. The proposed carrier ranking model was tested using real logistics performance data from major Ukrainian cities. The results demonstrate that the desirability-based approach improves the objectivity of carrier evaluation and allows regional differences in service performance to be considered.

Originality. The study proposes a hybrid approach to last-mile logistics management that integrates rule-based decision logic, data-driven analytics and multi-criteria optimisation using Harrington’s desirability function for carrier evaluation.

Practical value. The developed system can be applied in digital logistics platforms and e-commerce environments to improve delivery efficiency, automate carrier selection and adapt logistics decisions to regional service characteristics.

Keywords: Smart Logistics, last-mile delivery, carrier selection, logistics analytics

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