OMBORXONA LOGISTIKASIDA KO‘P ROBOTLI TIZIMLARNI TRANSPORT MASALASINI DINAMIK VAQT CHEKLOVLARI OSTIDA MODELLASHTIRISH

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Arxiv / №7 · 2026 / Maqola

OMBORXONA LOGISTIKASIDA KO‘P ROBOTLI TIZIMLARNI TRANSPORT MASALASINI DINAMIK VAQT CHEKLOVLARI OSTIDA MODELLASHTIRISH

Annotatsiya

O'ZBEKCHA

Ushbu maqolada omborxona logistikasida ko‘p robotli tizimlarda vazifalarni taqsim-lash masalasi transport masalasi asosida matematik modellashtirilgan. Modelda robotlar va vazifalar o‘rtasidagi moslik xarajatlar matritsasi orqali ifodalanib, vazifalarning bajarilishida vaqt cheklovlari (de-adline va kechikish jarimalari) hisobga olingan. Taklif etilgan yondashuvda klassik transport modeli ke-ngaytirilib, unga vaqtga bog‘liq cheklovlar va kechikish funksiyasi kiritilgan. Bu esa real omborxona sha-roitida buyurtmalarni o‘z vaqtida bajarish va resurslardan samarali foydalanish imkonini beradi.

Kalit so'zlar: omborxona logistikasi, ko‘p robotli tizimlar, shimoli-g‘arbiy burchak usuli, minimal elementlar usuli, potensiallar usuli, dinamik vaqt cheklovlari, kechikish jarimasi.

РУССКИЙ

. В данной статье рассматривается математическая модель распределения за-дач в многороботных системах складской логистики на основе транспортной задачи. В предло-женной модели соответствие между роботами и задачами представлено в виде матрицы затрат, а также учитываются временные ограничения (дедлайны и штрафы за задержку) при выполнении задач. Предложенный подход расширяет классическую транспортную модель за счёт введения временно-зависимых ограничений и функции штрафа за задержку. Это позволяет эффективно использовать ресурсы и обеспечивать своевременное выполнение заказов в реальных условиях складской логистики.

Ключевые слова: : складская логистика, многороботные системы, метод северо-западного угла, метод минимального элемента, метод потенциалов, динамические временные ограничения, штраф за задержку.

ENGLISH

This article presents a mathematical model of task allocation in multi-robot systems in warehouse logistics based on the transportation problem. In the proposed model, the correspondence between robots and tasks is represented using a cost matrix, and time constraints (deadlines and delay penalties) in task execution are taken into account. The proposed approach extends the classical trans-portation model by incorporating time-dependent constraints and a delay penalty function. This enables efficient utilization of resources and timely completion of orders in real warehouse environments.

Keywords: warehouse logistics, multi-robot systems, northwest corner method, least cost method, potential method, dynamic time constraints, delay penalty.

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Foydalanilgan adabiyotlar

Fragapane G., Hvolby H.-H., Sgarbossa F., Strandhagen J.O. Increasing warehouse efficiency by combi-ning internal transport and automated storage and retrieval systems. International Journal of Production Economics. 2020, vol. 226, Art. 107629. DOI: 10.1016/j.ijpe.2020.107629.
Palleschi A., Pollayil G.J., Pollayil M.J., Garabini M., Pallottino L. High-Level Planning for Object Manipulation With Multi Heterogeneous Robots in Shared Environments // IEEE Robotics and Automation Letters. 2022, vol. 7, № 2, p. 3138–3145. DOI: 10.1109/LRA.2022.3145987.
Wang J., Zheng S. Research on Path Planning Algorithms of Multiple Mobile Robots in Intelligent Warehousing. Proceedings of ICAROB 2022. 2022, p. 313–317. DOI: 10.5954/ICAROB.2022.OS34-1.
Huo J., Zheng R., Zhang S., Liu M. Multi-Robot Path Planning in Narrow Warehouse Environments with Fast Feasibility Heuristics. 41st Chinese Control Conference (CCC). 2022, p. 1840–1845. DOI: 10.23919/ CCC55666. 2022.9902480.
Chen J., Chen W., Li J., Wei X. va boshq. Path Planning Considering Time-Varying and Uncertain Move-ment Speed in Multi-Robot Automatic Warehouses: Problem Formulation and Algorithm // 2022 IEEE 8th Inter-national Conference on Cloud Computing and Intelligent Systems (CCIS). 2022, DOI: 10.1109/CCIS57298. 2022. 10016376
Inomova O.Sh. Transport masalasi yechimining avtomatlashtirilgan modeli. Python dasturlash tili aso-sidagi yondashuv. Yil tadqiqotchisi–2025. 2026, 2972–2984.-betlar URL: https://wordlyknowledge.uz/index.php/ gpble/ article/ view/ 5029/ 7699 (murojaat sanasi: 13.06.2026).

← Songa qaytish

[1] Fragapane G., Hvolby H.-H., Sgarbossa F., Strandhagen J.O. Increasing warehouse efficiency by combi-ning internal transport and automated storage and retrieval systems. International Journal of Production Economics. 2020, vol. 226, Art. 107629. DOI: 10.1016/j.ijpe.2020.107629.

[2] Palleschi A., Pollayil G.J., Pollayil M.J., Garabini M., Pallottino L. High-Level Planning for Object Manipulation With Multi Heterogeneous Robots in Shared Environments // IEEE Robotics and Automation Letters. 2022, vol. 7, № 2, p. 3138–3145. DOI: 10.1109/LRA.2022.3145987.

[3] Wang J., Zheng S. Research on Path Planning Algorithms of Multiple Mobile Robots in Intelligent Warehousing. Proceedings of ICAROB 2022. 2022, p. 313–317. DOI: 10.5954/ICAROB.2022.OS34-1.

[4] Huo J., Zheng R., Zhang S., Liu M. Multi-Robot Path Planning in Narrow Warehouse Environments with Fast Feasibility Heuristics. 41st Chinese Control Conference (CCC). 2022, p. 1840–1845. DOI: 10.23919/ CCC55666. 2022.9902480.

[5] Chen J., Chen W., Li J., Wei X. va boshq. Path Planning Considering Time-Varying and Uncertain Move-ment Speed in Multi-Robot Automatic Warehouses: Problem Formulation and Algorithm // 2022 IEEE 8th Inter-national Conference on Cloud Computing and Intelligent Systems (CCIS). 2022, DOI: 10.1109/CCIS57298. 2022. 10016376

[6] Inomova O.Sh. Transport masalasi yechimining avtomatlashtirilgan modeli. Python dasturlash tili aso-sidagi yondashuv. Yil tadqiqotchisi–2025. 2026, 2972–2984.-betlar URL: https://wordlyknowledge.uz/index.php/ gpble/ article/ view/ 5029/ 7699 (murojaat sanasi: 13.06.2026).