TRANSPORT-LOGISTIKA TIZIMLARIDA KO‘P MEZONLI OPTIMALLASHTIRISH MODELINI DINAMIK VAZN KOEFFITSIYENTLARI ASOSIDA TAKOMILLASHTIRISH
DOI:
https://doi.org/10.65164/ye35da40Kalit so‘zlar:
ko‘p mezonli optimallashtirish, vazn koeffitsiyentlari, transport xarajati, masofa, vaqt, maqbullashtirish modeli, Pareto optimallik.Abstrak
Ushbu maqolada transport-logistika tizimlarida transport xarajati, masofa va vaqt mezonlari asosida vazn koeffitsiyentlariga ega bo‘lgan ko‘p mezonli maqbullashtirish modelini takomillashtirish masalasi o‘rganiladi. Zamonaviy logistika tizimlarida bir vaqtning o‘zida bir nechta, ko‘pincha bir-biriga zid bo‘lgan maqsadlarni (xarajatlarni minimallashtirish, yetkazib berish vaqtini qisqartirish, masofani optimallashtirish) hisobga olish zarurati mavjud. Taklif etilayotgan modelda har bir mezonga ekspert baholashlar va statistik ma’lumotlar asosida aniqlanuvchi vazn koeffitsiyentlari berilgan bo‘lib, bu qaror qabul qiluvchining ustuvorliklarini moslashuvchan tarzda aks ettirish imkonini beradi. Modelni takomillashtirishning asosiy yo‘nalishlari: vazn koeffitsiyentlarini dinamik tarzda aniqlash mexanizmini ishlab chiqish, mezonlarni normallashtirishning yangi usulini joriy etish va Pareto-optimal yechimlarni izlash samaradorligini oshirishdan iborat. Tadqiqot natijalari shuni ko‘rsatadiki, takomillashtirilgan model transport marshrutlarini rejalashtirishda qaror qabul qilish jarayonining sifatini oshirish, xarajatlar va vaqt o‘rtasidagi optimal muvozanatni ta’minlash imkonini beradi.
Havolalar
[1] G‘aybullaev B.Q. Transport-logistika tizimini optimallashtirishda raqamli texnologiyalarning iqtisodiy samaradorligi (Buxoro logistika markazi misolida) // Science and Education. – 2026. – Vol. 7, No. 2. – P. 501–510.
[2] Oguntola I.O., Ülkü M.A., Saif A., Engau A. On the value of shipment consolidation and machine learning techniques for the optimal design of a multimodal logistics network // INFOR: Information Systems and Operational Research. – 2024. – Vol. 62, No. 1. – P. 1–52.
[3] Gryshchuk O., Petryk A., Kopiak N., Litus T. Transport and logistics service of foreign trade cargo flows in integrated production systems // MATEC Web of Conferences. – 2024. – Vol. 392. – P. 03002.
[4] Borzenkov A.M., Pronin C.B., Podberezkin A.A., Ostroukh A.V., Shmonin A.M. Research methods for multicriteria optimization of logistics based on hybrid evolutionary-predictive models // Journal of Applied Engineering Science. – 2025. – Vol. 15, No. 4. – P. 285–306.
[5] T.B. Djuraev, Н.К. Чориёров Модель информационных потоков в диспетчерской службе транспортного процесса. Journal of Integrated Education and Research. Vol. 1 No. 6 (2022): б. 63-67.
[6] J.T. Usmonov, T.B. Djurayev, Pulatova Z.M. Imitation models of the railway organization for railway transport flows, International Conference on Information Science andCommunications Technologies: Applications, Trends and Opportunities, ICISCT 2021.DOI: 10.1109/ICISCT52966.2021.9670044 Retrieved from www.scopus.com
[7] J.T. Usmonov, T.B. Djurayev Technical science and innovation, Imitation models of the railway organization for railway transport flows, Tashkent state technical university named after Islam Karimov., №4(10) tashkent 2021 page 201-207.
[8] T.B Djuraev, O.X. Alloyorov “Автомобил транспорти логистикаси фаолиятини Монте-карло усули асосида оптималлаштириш”. “Muhammad al-Xorazmiy avlodlari” ilmiyamaliy va axborot-tahliliy jurnali. 2(16) /2021, 46-51
[9] J.T. Usmonov, T.B. Djuraev, Z.M. Pulatova (2020). Optimization of global information flows in transport system management. Journal of Advanced Research in Dynamical and Control Systems, 12(7 Special Issue), 2024-2032. doi:10.5373/JARDCS/V12SP7/20202319 Retrieved from www.scopus.com
[10] X. Jiyanbekov, J. Usmonov, S. Azimov (2019). The probability model of railway transport system activity. Paper presented at the Transport Means - Proceedings of the International Conference, 2019- October 1256-1259.
