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Optimizing a vendor managed inventory (VMI) model considering delivering cost in a three-echelon supply chain using two tuned-parameter meta-heuristics

An ISM based framework for structural relationship among various manufacturing flexibility dimensions

International Journal of System Assurance Engineering and Management : Volume 6, Issue 3, September 2015

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International Journal of System Assurance Engineering and Management : Volume 6, Issue 1, March 2015

International Journal of System Assurance Engineering and Management : Volume 5

International Journal of System Assurance Engineering and Management : Volume 4

International Journal of System Assurance Engineering and Management : Volume 3

International Journal of System Assurance Engineering and Management : Volume 2

International Journal of System Assurance Engineering and Management : Volume 1

Optimizing a vendor managed inventory (VMI) model considering delivering cost in a three-echelon supply chain using two tuned-parameter meta-heuristics

Content Provider	Springer Nature Link
Author	Sadeghi, Javad Taghizadeh, Mahziar Sadeghi, Ahamd Jahangard, Reza Tavakkoli Moghaddam, Reza
Copyright Year	2014
Abstract	In the retailer-supplier partnerships, the vendor-managed inventory (VMI) is one of the important policies in the supply chain management (SCM) to reduce the bullwhip effect. As there is a lack of study on the central warehouse via delivering cost in VMI literature, this paper presents a VMI model in SCM including single-vendor, multi-retailer, and single-warehouse. While the vendor confronts with two constraints, namely the number of orders and budget, the purpose of this research is to find order size, the shortest possible route, and replenishment frequencies for the vendor and the retailers to minimize the total inventory cost. As the proposed model is an NP-hard problem, a meta-heuristics namely particle swarm optimization (PSO) is employed to optimize the proposed model. Since there is no available benchmark for evaluation of the proposed method, a genetic algorithm is used to validate and verify the solution presented by PSO. Moreover, Taguchi method in the design of experiments calibrates the parameters of the algorithm to provide the reliable solution. Finally, the conclusion and further studies are presented.
Starting Page	500
Ending Page	510
Page Count	11
File Format	PDF
ISSN	09756809
Journal	International Journal of System Assurance Engineering and Management
Volume Number	6
Issue Number	4
e-ISSN	09764348
Language	English
Publisher	Springer India
Publisher Date	2014-11-09
Publisher Place	New Delhi
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Inventory model Delivering costs Tuned–parameter particle swarm optimization (PSO) Tuned–parameter genetic algorithm (GA) Central warehouse Quality Control, Reliability, Safety and Risk Engineering Economics, Organization, Logistics, Marketing
Content Type	Text
Resource Type	Article
Subject	Strategy and Management Safety, Risk, Reliability and Quality

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