International Journal of Industrial Engineering & Production Research
Iran University of Science & Technology
Tue, Jul 16, 2024
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Volume 29, Issue 3 (IJIEPR 2018)
IJIEPR 2018, 29(3): 377-399 |
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Khalifehzadeh S, Fakhrzad M B. A stochastic multi objective mathematical model to optimize a production and distribution system with stochastic demand and stochastic lead time. IJIEPR 2018; 29 (3) :377-399
URL: http://ijiepr.iust.ac.ir/article-1-833-en.html
URL: http://ijiepr.iust.ac.ir/article-1-833-en.html
1- Department of Industrial Engineering, Faculty of Engineering, Yazd University, Yazd, Iran
2- Department of Industrial Engineering, Faculty of Engineering, Yazd University, Yazd, Iran ,mfakhrzad@yazd.ac.ir
2- Department of Industrial Engineering, Faculty of Engineering, Yazd University, Yazd, Iran ,
Abstract: (4313 Views)
Abstract
Production and distribution network (PDN) planning in multi-stage status is commonly complex. These conditions cause significant amount of uncertainty relating to demand and lead time. In this study, we introduce a PDN to deliver the products to customers in the least time and optimize the total cost of the network, simultaneously. The proposed network is four stage PDN including suppliers, producers, potential entrepots, retailers and customers with multi time period horizon with allowable shortage. A mixed integer programming model with minimizing total cost of the system and minimizing total delivery lead time is designed. We present a novel heuristic method called selective firefly algorithm (SFA) in order to solve several sized especially real world instances. In SFA, each firefly recognizes all better fireflies with more brightness and analyses its brightness change before moving, tacitly. Then, the firefly that makes best change is selected and initial firefly moves toward the selected firefly. Finally, the performance of the proposed algorithm is examined with solving several sized instances. The results indicate the adequate performance of the proposed algorithm.
Production and distribution network (PDN) planning in multi-stage status is commonly complex. These conditions cause significant amount of uncertainty relating to demand and lead time. In this study, we introduce a PDN to deliver the products to customers in the least time and optimize the total cost of the network, simultaneously. The proposed network is four stage PDN including suppliers, producers, potential entrepots, retailers and customers with multi time period horizon with allowable shortage. A mixed integer programming model with minimizing total cost of the system and minimizing total delivery lead time is designed. We present a novel heuristic method called selective firefly algorithm (SFA) in order to solve several sized especially real world instances. In SFA, each firefly recognizes all better fireflies with more brightness and analyses its brightness change before moving, tacitly. Then, the firefly that makes best change is selected and initial firefly moves toward the selected firefly. Finally, the performance of the proposed algorithm is examined with solving several sized instances. The results indicate the adequate performance of the proposed algorithm.
Keywords: Supply chain Management, Multi Objective programming Model, multi transportation systems, Selective Firefly Algorithm (SFA), probabilistic demand, probabilistic delivery lead time.
Type of Study: Research |
Subject:
Operations Research
Received: 2018/06/5 | Accepted: 2018/10/22 | Published: 2018/10/22
Received: 2018/06/5 | Accepted: 2018/10/22 | Published: 2018/10/22
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