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Journals / Uludağ Üniversitesi Mühendislik Fakültesi Dergisi / 2026 / Cilt: 23 Sayı: 4 Özel Sayı

Multi-Product Inventory Location-Routing Problem with Shortages

KARŞILANAMAYAN TALEPLİ ÇOKLU ÜRÜN ENVANTER YERLEŞİM VE ROTALAMA PROBLEMİ

Özge Şatır Akpunar(MANİSA CELÂL BAYAR ÜNİVERSİTESİ)
Şener Akpınar(Dokuz Eylül Üniversitesi)
Pages
177–192
Publication Date
2018-12-31
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The best known results in the literature have been found or the best results have been approached for both problem dataset.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The companies, who wants to adapt to the changed market conditions and remain competitive, have to manage their storage and distribution processes in a cost effective manner as well as their production processes.
📊
Key Findings & Data:The logistic costs consume a significant part of the budget of the companies and therefore these processes must be managed as efficiently as possible.
💡
Conclusion & Impact:The best known results in the literature have been found or the best results have been approached for both problem dataset.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Büyük komşuluk arama algoritması · Envanter yerleşim ve rotalama problemi · Hatalı ürünler

Abstract

The companies, who wants to adapt to the changed market conditions and remain competitive, have to manage their storage and distribution processes in a cost effective manner as well as their production processes. The logistic costs consume a significant part of the budget of the companies and therefore these processes must be managed as efficiently as possible. The design of such an effective logistic network contains two hard combinatorial optimization problems, to locate facilities, and to determine vehicle routes supplying demand points from these locations. Within the context of this study, we deal with the Location Inventory Routing Problem (LIRP), which is an enriched Location Routing Problem (LRP) with the inventory related issues and determines inventory, location and transportation related decisions at the strategic, tactical and operational levels. A mathematical model, a combination of a location-routing problem and a joint replenishment economic order quantity (EOQ) model with backorders, is developed to formally describe the problem. Large neighborhood search algorithm is developed to solve the problem. Comparative results with the location-routing problem data sets from the literature is used in order to evaluate solution method. The best known results in the literature have been found or the best results have been approached for both problem dataset.

Özet

Şirketler, değişen market koşullarına adapte olmak ve rekabet içinde kalmak için lojistik faaliyetlerini de üretim faaliyetleri gibi iyi bir şekilde yönetmelidir. Lojistik maliyetleri, şirket maliyetlerinin büyük bir kısmını oluşturduğu için etkin bir şekilde yönetilmelidir. Etkin bir lojistik ağı oluşturulurken üretim birimlerinin yerleşimi ve bu birimlerden talep noktalarına giden araç rotalarına karar verilmesi karşılaşılan ve çözülmesi gereken optimizasyon problemleridir. Bu çalışma kapsamında envanter, yerleşim ve rotalama ile ilgili kararlar göz önüne alınarak bir yerleşim-envanter-rotalama probleminin çözülmesi amaçlanmıştır. Yerleşim-rotalama problemi ile karşılanamayan talepli ekonomik üretim miktarı modeli entegre edilerek problemin formülasyonu oluşturulmuştur. Problemin çözümü için bir büyük komşuluk arama algoritması geliştirilmiştir. Algoritmanın değerlendirilmesi, literatürden alınan yerleşim-rotalama problem veri setleri ile yapılan karşılaştırmalı sonuçlar aracılığıyla gerçekleştirilmiştir. Literatürde her iki problem veri seti için de bilinen en iyi sonuçlar bulunmuş veya en iyi sonuçlara yaklaşılmıştır.

🔖

Cite This Article

Akpunar, Ö. Ş., Akpınar, Ş. (2018). Multi-Product Inventory Location-Routing Problem with Shortages. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, Cilt: 23 Sayı: 4 Özel Sayı, 177–192. https://doi.org/10.17482/uumfd.455229

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