Current Proceedings on Technology

Yazarlar: Esra Kahyaoglu, Gokcen Turkel, Gulgun Kayakutlu

Konular:-

Anahtar Kelimeler:Artificial intelligence,Dynamical systems,Supplier effect,Scheduling

Özet: Dynamic scheduling is an indispensable need in today’s competitive business world. Delivery performance andsupplier management including procurement activities have crucial impact to satisfy the customer. Supply chainmanagement performance can be improved by the quality and perfect timing of logistics activities.This studyaims to propose a model to predict minimum delivery delay depending on supplier performance in procurement.This is an NP-complete problem that benefits the historical effects in order to constitute the future plans. Factorsinfluencing the delivery and procurement processes are depicted from various researches in the field andimproved with the contributions of experts from a global company. Prediction is modeled as an Artificial NeuralNetwork (ANN) using Back Propagation (BP) learning. The proposed model adapts to the changes by forecastingthe amount of deviation from the existing plans. The model is applied in a case study of light commercial vehicledeliveries. Solutions of BP are compared. Achievements of this study will not only contribute to the research, butwill open a new dimension in the logistics vision.

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