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akaturk Akademik ölçüm

Makale detayı · 2020

A novel hybrid artificial intelligence-based decision support framework to predict lead time

International Journal of Logistics Research and Applications

YÖKSİS OpenAlex SJR Q1 JCR Q3 Atıf 21 Yüzdelik 87.0% FWCI 1.87
Yıl
2020
ISSN
1367-5567
Tür
article

Veri kaynağı ayrımı

  • YÖKSİS YÖKSİS makale kaydı
  • OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)

Özet

İngilizce (OpenAlex)

Inventory and routing are the two most important elements to company’s survival in supply chain environments. Hence, solution approaches of inventory routing problem (IRP) should assure adequate inventory level and also provide an efficient route. In this case, hybrid approaches can empower researchers to solve the IRP. The aim of this study is to develop a new hybrid methodology that includes two phases to provide a generic framework for IRP. In Phase I, genetic algorithm-based simulation optimisation is used to dynamically perform inventory control and routing decisions. In Phase II, artificial intelligence (AI)-based simulation in which the lead time of supply chain members is predicted is employed to extend the functionality of the method in Phase I. The proposed hybrid methodology gives insights into the cross-fertilisation of AI, simulation, and optimisation for researchers. Therefore, this integration can be applied to different supply chain problems by using similar methods.

Konular

  • Vehicle Routing Optimization Methods
  • Advanced Manufacturing and Logistics Optimization
  • Optimization and Packing Problems

Birincil konu Vehicle Routing Optimization Methods

Yazarlar

  1. AYŞE TUĞBA DOSDOĞRU
  2. ASLI BORU İPEK
  3. MUSTAFA GÖÇKEN ADANA ALPARSLAN TÜRKEŞ BİLİM VE TEKNOLOJİ ÜNİVERSİTESİ